Réalta Technologies Joins TDengine Partner Network as a Value-Added Reseller

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Réalta Technologies Joins TDengine Partner Network as a Value-Added Reseller

TDengine today announced that Réalta Technologies, an Ireland-based global automation and digital systems integrator, has joined the TDengine Reseller Program as a value-added reseller (VAR). The partnership expands TDengine’s worldwide ecosystem and strengthens its ability to deliver high-performance time-series and industrial data solutions to manufacturing and life sciences customers.

 

Through this collaboration, Réalta will offer TDengine’s industry-leading time-series database and AI-native industrial data management platform to enterprises across pharmaceutical, biopharmaceutical, medical device, FMCG, and general manufacturing sectors. As a value-added reseller, Réalta will provide deep expertise in automation, data infrastructure, analytics, and integration, helping clients modernize operations and accelerate Industry 4.0 adoption.

 

“TDengine is revolutionizing how industrial data is collected, stored, and analyzed,” said Jim Fan, VP of Product at TDengine. “Réalta Technologies’ broad experience in digital systems integration and process optimization makes them an exceptional partner to extend TDengine’s reach and help customers achieve faster, more data-driven operations.”

 

Réalta Technologies is a global automation and digital systems integrator headquartered in Cork, Ireland, with offices in Cork, the United States, and India. The company provides automation, digitalization, and data analytics solutions for the life sciences, pharmaceutical, manufacturing, and other industries. With deep expertise across engineering, industrial automation, IT systems, and data infrastructure, Réalta helps clients maximize the value of their data and achieve true Industry 4.0 transformation.

 

“We’re proud to partner with TDengine to bring their innovative time-series data technology to our clients,” said Dan Moore, CEO of Réalta Technologies. “Our mission is to help organizations harness the full power of their data and drive manufacturing excellence from automation to analytics. With TDengine’s platform for operational data storage and management, we can deliver even greater value through performance, scalability, and real-time intelligence.”

 

By combining Réalta’s global presence and industry expertise with TDengine’s high-performance, AI-native industrial data platform, customers will benefit from streamlined deployments, simplified operations, and a lower total cost of ownership across on-premises, cloud, and hybrid environments.

Réalta Technologies Joins TDengine Partner Network as a Value-Added Reseller

Réalta Technologies Joins TDengine Partner Network as a Value-Added Reseller

TDengine today announced that Réalta Technologies, an Ireland-based global automation and digital systems integrator, has joined the TDengine Reseller Program as a value-added reseller (VAR). The partnership expands TDengine’s worldwide ecosystem and strengthens its ability to deliver high-performance time-series and industrial data solutions to manufacturing and life sciences customers.

 

Through this collaboration, Réalta will offer TDengine’s industry-leading time-series database and AI-native industrial data management platform to enterprises across pharmaceutical, biopharmaceutical, medical device, FMCG, and general manufacturing sectors. As a value-added reseller, Réalta will provide deep expertise in automation, data infrastructure, analytics, and integration, helping clients modernize operations and accelerate Industry 4.0 adoption.

 

“TDengine is revolutionizing how industrial data is collected, stored, and analyzed,” said Jim Fan, VP of Product at TDengine. “Réalta Technologies’ broad experience in digital systems integration and process optimization makes them an exceptional partner to extend TDengine’s reach and help customers achieve faster, more data-driven operations.”

 

Réalta Technologies is a global automation and digital systems integrator headquartered in Cork, Ireland, with offices in Cork, the United States, and India. The company provides automation, digitalization, and data analytics solutions for the life sciences, pharmaceutical, manufacturing, and other industries. With deep expertise across engineering, industrial automation, IT systems, and data infrastructure, Réalta helps clients maximize the value of their data and achieve true Industry 4.0 transformation.

 

“We’re proud to partner with TDengine to bring their innovative time-series data technology to our clients,” said Dan Moore, CEO of Réalta Technologies. “Our mission is to help organizations harness the full power of their data and drive manufacturing excellence from automation to analytics. With TDengine’s platform for operational data storage and management, we can deliver even greater value through performance, scalability, and real-time intelligence.”

 

By combining Réalta’s global presence and industry expertise with TDengine’s high-performance, AI-native industrial data platform, customers will benefit from streamlined deployments, simplified operations, and a lower total cost of ownership across on-premises, cloud, and hybrid environments.

Réalta Technologies Joins TDengine Partner Network as a Value-Added Reseller

Réalta Technologies Joins TDengine Partner Network as a Value-Added Reseller Read More »

Data Historian Spotlight: Canary Historian’s Role in Life Sciences

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Data Historian Spotlight: Canary Historian’s Role in Life Sciences

Introduction: 

In the world of pharmaceutical and life sciences manufacturing, the ability to capture, contextualise, and analyse data in real time is essential. Modern operations depend on reliable, validated data systems that not only meet strict compliance standards but also empower continuous improvement, efficiency, and innovation. Among the leading data historian technologies driving this transformation is Canary Historian, a powerful, scalable solution trusted by manufacturers worldwide.

As specialists in data infrastructure and data analytics, Réalta Technologies works closely with clients to implement historian systems like Canary, helping them achieve visibility, reliability, and data integrity across their operations.

 

What Is Canary Historian?

Canary Historian, developed by Canary Labs, is a high-performance, enterprise-grade data historian designed to store, manage, and analyse time-series data. Built for speed, reliability, and scalability, it provides life sciences organisations with a secure and compliant platform for collecting data from sensors, control systems, and industrial devices.

Unlike traditional historians that can be complex to maintain or scale, Canary’s architecture is lightweight and efficient, allowing for fast data ingestion and retrieval without compromising integrity or performance. It seamlessly integrates with control systems like Siemens, Rockwell, Emerson, and Ignition front end screens, as well as analytics and reporting platforms such as Power BI and SEEQ.

 

Key Capabilities of Canary Historian

Canary Historian is built with a clear focus on data integrity, speed, and accessibility, all essential criteria in regulated environments such as pharmaceutical manufacturing.

  • Lossless Data Compression:
    Canary’s patented compression algorithms allow massive volumes of process data to be stored efficiently while preserving accuracy. This ensures traceability and compliance with regulatory frameworks like FDA 21 CFR Part 11 and EU Annex 11.
  • High-Performance Data Retrieval:
    Canary is optimised for fast query performance, enabling engineers, data scientists, and quality teams to access and visualise data instantly, even across years of historical information.
  • Scalability and Flexibility:
    Designed to scale from a single production line to global enterprise deployments, Canary can handle millions of data points per second, supporting digital transformation initiatives across multiple sites.
  • Integration with Analytics Platforms:
    Through seamless integration with SEEQ, Power BI, and other modern analytics tools, Canary allows users to move from raw process data to actionable insights. Additionally, Canary can integrate its UNS architecture seamlessly by collecting data in MQTT & SPBv1.0 specifications from MQTT data sources.
    This empowers smarter decision-making and accelerates continuous improvement. 
  • Security and Compliance:
    Canary supports role-based access control, data encryption, and full audit trails , critical for compliance in GxP environments.

 

Use Cases in Life Sciences and Pharmaceutical Manufacturing

For pharmaceutical and biotech manufacturers, data integrity and process optimisation are non-negotiable. Canary Historian plays a crucial role across a range of applications:

  • Batch Process Monitoring:
    Ensuring each batch follows the defined recipe and identifying deviations or anomalies early in production.
  • Equipment Performance Tracking:
    Continuous monitoring of critical systems such as bioreactors, cleanrooms, and HVAC to ensure operational reliability and product quality.
  • Regulatory Compliance and Audit Readiness:
    Providing detailed data trails that demonstrate compliance with GMP standards and regulatory requirements.
  • Energy and Utility Management:
    Capturing and analysing utility data, from compressed air to chilled water, to optimise energy consumption and sustainability initiatives.
  • Predictive Maintenance and Quality Analytics:
    When combined with advanced analytics platforms, Canary enables manufacturers to predict equipment failures before they occur and improve product consistency through process insights.

 

Data Collection, Visualisation, and Analytics

At its core, Canary is more than a historian, it is a data foundation for innovation. By centralising time-series data and contextualising it within the manufacturing ecosystem, it enables seamless visualisation and analysis.

Through integrations with platforms like SEEQ, engineers can build advanced analytics models, track key performance indicators (KPIs), and uncover correlations between process parameters and product quality. This real-time visibility leads to more efficient operations, reduced downtime, and data-driven decision-making across departments.

 

How Réalta Technologies Adds Value with Canary Historian

As a trusted data partner to global life sciences organisations, Réalta Technologies has extensive experience implementing and optimising Canary Historian systems. Our engineers understand both the technical and regulatory dimensions of data management, ensuring that each deployment is compliant, scalable, and future-ready.

Our expertise spans:

  • Designing and deploying data historian architectures across multi-site facilities.
  • Integrating Canary with control systems and enterprise applications.
  • Enabling connectivity to SEEQ, Power BI, and advanced analytics frameworks.
  • Supporting validation, testing, and documentation to meet regulatory expectations.

Whether you are upgrading from legacy historians or implementing a new data infrastructure, Réalta Technologies provides a complete solution , from design and deployment to ongoing managed services.

 

Conclusion

In today’s data-driven manufacturing landscape, the ability to collect, contextualise, and analyse process data efficiently is a competitive advantage. Canary Historian provides life sciences companies with the flexibility, speed, and compliance they need to turn data into real value.

Partnering with Réalta Technologies ensures that this technology is implemented with precision and aligned with your business goals. With proven expertise in data historians, automation, and analytics, we empower organisations to achieve operational excellence through data.

 

To learn more about how Réalta Technologies can help you implement or optimise Canary Historian, contact our team today.

📧 [email protected]
💻 https://realtatechnologies.com
📞 IRL: +353 21 243 9113 | US: +1 302 509 4401

Data Historian Spotlight: Canary Historian’s Role in Life Sciences

Data Historian Spotlight: Canary Historian’s Role in Life Sciences

Introduction: 

In the world of pharmaceutical and life sciences manufacturing, the ability to capture, contextualise, and analyse data in real time is essential. Modern operations depend on reliable, validated data systems that not only meet strict compliance standards but also empower continuous improvement, efficiency, and innovation. Among the leading data historian technologies driving this transformation is Canary Historian, a powerful, scalable solution trusted by manufacturers worldwide.

As specialists in data infrastructure and data analytics, Réalta Technologies works closely with clients to implement historian systems like Canary, helping them achieve visibility, reliability, and data integrity across their operations.

 

What Is Canary Historian?

Canary Historian, developed by Canary Labs, is a high-performance, enterprise-grade data historian designed to store, manage, and analyse time-series data. Built for speed, reliability, and scalability, it provides life sciences organisations with a secure and compliant platform for collecting data from sensors, control systems, and industrial devices.

Unlike traditional historians that can be complex to maintain or scale, Canary’s architecture is lightweight and efficient, allowing for fast data ingestion and retrieval without compromising integrity or performance. It seamlessly integrates with control systems like Siemens, Rockwell, Emerson, and Ignition front end screens, as well as analytics and reporting platforms such as Power BI and SEEQ.

 

Key Capabilities of Canary Historian

Canary Historian is built with a clear focus on data integrity, speed, and accessibility, all essential criteria in regulated environments such as pharmaceutical manufacturing.

  • Lossless Data Compression:
    Canary’s patented compression algorithms allow massive volumes of process data to be stored efficiently while preserving accuracy. This ensures traceability and compliance with regulatory frameworks like FDA 21 CFR Part 11 and EU Annex 11.
  • High-Performance Data Retrieval:
    Canary is optimised for fast query performance, enabling engineers, data scientists, and quality teams to access and visualise data instantly, even across years of historical information.
  • Scalability and Flexibility:
    Designed to scale from a single production line to global enterprise deployments, Canary can handle millions of data points per second, supporting digital transformation initiatives across multiple sites.
  • Integration with Analytics Platforms:
    Through seamless integration with SEEQ, Power BI, and other modern analytics tools, Canary allows users to move from raw process data to actionable insights. Additionally, Canary can integrate its UNS architecture seamlessly by collecting data in MQTT & SPBv1.0 specifications from MQTT data sources.
    This empowers smarter decision-making and accelerates continuous improvement. 
  • Security and Compliance:
    Canary supports role-based access control, data encryption, and full audit trails , critical for compliance in GxP environments.

 

Use Cases in Life Sciences and Pharmaceutical Manufacturing

For pharmaceutical and biotech manufacturers, data integrity and process optimisation are non-negotiable. Canary Historian plays a crucial role across a range of applications:

  • Batch Process Monitoring:
    Ensuring each batch follows the defined recipe and identifying deviations or anomalies early in production.
  • Equipment Performance Tracking:
    Continuous monitoring of critical systems such as bioreactors, cleanrooms, and HVAC to ensure operational reliability and product quality.
  • Regulatory Compliance and Audit Readiness:
    Providing detailed data trails that demonstrate compliance with GMP standards and regulatory requirements.
  • Energy and Utility Management:
    Capturing and analysing utility data, from compressed air to chilled water, to optimise energy consumption and sustainability initiatives.
  • Predictive Maintenance and Quality Analytics:
    When combined with advanced analytics platforms, Canary enables manufacturers to predict equipment failures before they occur and improve product consistency through process insights.

 

Data Collection, Visualisation, and Analytics

At its core, Canary is more than a historian, it is a data foundation for innovation. By centralising time-series data and contextualising it within the manufacturing ecosystem, it enables seamless visualisation and analysis.

Through integrations with platforms like SEEQ, engineers can build advanced analytics models, track key performance indicators (KPIs), and uncover correlations between process parameters and product quality. This real-time visibility leads to more efficient operations, reduced downtime, and data-driven decision-making across departments.

 

How Réalta Technologies Adds Value with Canary Historian

As a trusted data partner to global life sciences organisations, Réalta Technologies has extensive experience implementing and optimising Canary Historian systems. Our engineers understand both the technical and regulatory dimensions of data management, ensuring that each deployment is compliant, scalable, and future-ready.

Our expertise spans:

  • Designing and deploying data historian architectures across multi-site facilities.
  • Integrating Canary with control systems and enterprise applications.
  • Enabling connectivity to SEEQ, Power BI, and advanced analytics frameworks.
  • Supporting validation, testing, and documentation to meet regulatory expectations.

Whether you are upgrading from legacy historians or implementing a new data infrastructure, Réalta Technologies provides a complete solution , from design and deployment to ongoing managed services.

 

Conclusion

In today’s data-driven manufacturing landscape, the ability to collect, contextualise, and analyse process data efficiently is a competitive advantage. Canary Historian provides life sciences companies with the flexibility, speed, and compliance they need to turn data into real value.

Partnering with Réalta Technologies ensures that this technology is implemented with precision and aligned with your business goals. With proven expertise in data historians, automation, and analytics, we empower organisations to achieve operational excellence through data.

 

To learn more about how Réalta Technologies can help you implement or optimise Canary Historian, contact our team today.

📧 [email protected]
💻 https://realtatechnologies.com
📞 IRL: +353 21 243 9113 | US: +1 302 509 4401

Data Historian Spotlight: Canary Historian’s Role in Life Sciences

Data Historian Spotlight: Canary Historian’s Role in Life Sciences Read More »

Turning Data into Action: Réalta Technologies Hosts Industry and Sport Event at Thomond Park

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Turning Data into Action: Réalta Technologies Hosts Industry and Sport Event at Thomond Park

Introduction: 

Réalta Technologies recently hosted an exclusive event at Thomond Park, home of Munster Rugby, exploring how data is driving performance and decision-making across both industry and sport. The event, Turning Data into Action: Unlocking Real-Time Insights for Operational Excellence in Industry and Sport, brought together clients, partners, and industry leaders for an engaging day of learning, collaboration, and discussion.

Guests enjoyed a behind-the-scenes tour of Thomond Park and a series of presentations and panel discussions featuring thought leaders from Réalta Technologies, AVEVA, SolutionsPT, and Munster Rugby.

 

Shaping the Future with Digital Twins – Andy Davidson, AVEVA

Andy Davidson, Product Manager at AVEVA, opened the day with an insightful session on Building and Evolving a Digital Twin. He explained how digital twins bring together connected data and intelligent insight to improve decision-making, efficiency, and performance. Andy highlighted how these technologies are already transforming industries and how AVEVA’s scalable digital solutions empower businesses of all sizes to operate more intelligently.

 

Digitalisation of the 3D Printing Process – Declan Hickey, Réalta Technologies

Declan Hickey, Principal Engineer at Réalta Technologies, delivered an engaging session on Digitalisation of the 3D Printing Process. Declan explored how automation, data integration, and digital workflows can transform additive manufacturing, improving traceability, quality, and efficiency at every stage. 

He outlined how connecting equipment, materials, and production data within a unified digital framework enables manufacturers to achieve greater consistency, scalability, and regulatory compliance. Drawing on Réalta’s extensive experience in life sciences and advanced manufacturing, Declan demonstrated how a data-driven approach can unlock the full potential of 3D printing in regulated industries.

 

AI in Life Sciences – Thomas McCarthy, AVEVA

Next, Thomas McCarthy, Industry Principal at AVEVA, delivered a compelling talk on Artificial Intelligence in Life Sciences. Thomas outlined how AI and data integration are revolutionising the pharmaceutical sector, from pre-clinical research and development through to manufacturing and patient outcomes. His talk showcased how AI-driven data ecosystems can accelerate innovation, enhance quality, and optimise operations across the life sciences value chain.

 

From Equipment to Enterprise: Achieving Data Integration at a Global Scale – Réalta Technologies & Pharma Client

Nikhil Ramisetty and Andreas Scannell from Réalta Technologies were joined by a Value Stream Leader from a leading pharmaceutical client to deliver an insightful joint presentation on their collaborative work. Titled “From Equipment to Enterprise: Achieving Data Integration at a Global Scale:, the session detailed their shared journey in implementing a full-scale, GxP-compliant AVEVA PI System and advanced data analytics solution across the client sites. 

Together, they outlined how a unified data infrastructure can transform visibility, efficiency, and decision-making across complex operations. The speakers discussed the project’s key challenges, the importance of collaboration, and how the integration of data from equipment to enterprise level enables greater standardisation, compliance, and operational excellence in regulated environments.

 

Generative AI and Large Language Models – Ken Molloy, SolutionsPT

Ken Molloy, Customer Success Manager at SolutionsPT, delivered an engaging session on Generative AI and Large Language Models, examining the rapid advancements reshaping today’s industrial landscape. Ken provided an in-depth look at how generative AI is already driving innovation, efficiency, and smarter automation across industries. He also highlighted how SolutionsPT supports organisations through comprehensive education, training, audits, consulting, and customer success management, empowering teams to adapt, evolve, and succeed with confidence.

 

Data in Sport – George Murray & Munster Rugby

George Murray, Lead Performance Analyst for Munster Rugby, shared fascinating insights into how data analysis supports high performance within elite sport. He was joined by Damien Falvey of Réalta Technologies to discuss Munster’s data-driven approach and how Réalta Technologies are helping coaches and players optimise performance, manage workloads, and gain competitive advantage, illustrating clear parallels between how data delivers value both on the pitch and in industry.

The event concluded with a panel discussion hosted by Barry Murphy, former Munster Rugby player, who was joined by Munster Rugby coaches and players to gain an insight into how they use data to improve their performance and find that extra 1% in competitive edge. 

 

A Collaborative Success

Réalta Technologies would like to extend sincere thanks to AVEVA and SolutionsPT for their sponsorship and support in making the day possible, to Munster Rugby for their hospitality and partnership, and to all who attended and contributed to such a successful event.

Finally, a special thanks to the Réalta Technologies team whose effort and expertise made the event a resounding success. A special thanks to Damien Falvey, Nikhil Ramisetty, Andreas Scannell, and Declan Hickey for representing Réalta on stage and sharing their expertise with the audience.

Réalta looks forward to hosting more events that bring together leaders across industry and sport to explore how data can unlock the next era of innovation and performance.

Turning Data into Action: Réalta Technologies Hosts Industry and Sport Event at Thomond Park

Turning Data into Action: Réalta Technologies Hosts Industry and Sport Event at Thomond Park

Introduction: 

Réalta Technologies recently hosted an exclusive event at Thomond Park, home of Munster Rugby, exploring how data is driving performance and decision-making across both industry and sport. The event, Turning Data into Action: Unlocking Real-Time Insights for Operational Excellence in Industry and Sport, brought together clients, partners, and industry leaders for an engaging day of learning, collaboration, and discussion.

Guests enjoyed a behind-the-scenes tour of Thomond Park and a series of presentations and panel discussions featuring thought leaders from Réalta Technologies, AVEVA, SolutionsPT, and Munster Rugby.

 

Shaping the Future with Digital Twins – Andy Davidson, AVEVA

Andy Davidson, Product Manager at AVEVA, opened the day with an insightful session on Building and Evolving a Digital Twin. He explained how digital twins bring together connected data and intelligent insight to improve decision-making, efficiency, and performance. Andy highlighted how these technologies are already transforming industries and how AVEVA’s scalable digital solutions empower businesses of all sizes to operate more intelligently.

 

Digitalisation of the 3D Printing Process – Declan Hickey, Réalta Technologies

Declan Hickey, Principal Engineer at Réalta Technologies, delivered an engaging session on Digitalisation of the 3D Printing Process. Declan explored how automation, data integration, and digital workflows can transform additive manufacturing, improving traceability, quality, and efficiency at every stage. 

He outlined how connecting equipment, materials, and production data within a unified digital framework enables manufacturers to achieve greater consistency, scalability, and regulatory compliance. Drawing on Réalta’s extensive experience in life sciences and advanced manufacturing, Declan demonstrated how a data-driven approach can unlock the full potential of 3D printing in regulated industries.

 

AI in Life Sciences – Thomas McCarthy, AVEVA

Next, Thomas McCarthy, Industry Principal at AVEVA, delivered a compelling talk on Artificial Intelligence in Life Sciences. Thomas outlined how AI and data integration are revolutionising the pharmaceutical sector, from pre-clinical research and development through to manufacturing and patient outcomes. His talk showcased how AI-driven data ecosystems can accelerate innovation, enhance quality, and optimise operations across the life sciences value chain.

 

From Equipment to Enterprise: Achieving Data Integration at a Global Scale – Réalta Technologies & Pharma Client

Nikhil Ramisetty and Andreas Scannell from Réalta Technologies were joined by a Value Stream Leader from a leading pharmaceutical client to deliver an insightful joint presentation on their collaborative work. Titled “From Equipment to Enterprise: Achieving Data Integration at a Global Scale:, the session detailed their shared journey in implementing a full-scale, GxP-compliant AVEVA PI System and advanced data analytics solution across the client sites. 

Together, they outlined how a unified data infrastructure can transform visibility, efficiency, and decision-making across complex operations. The speakers discussed the project’s key challenges, the importance of collaboration, and how the integration of data from equipment to enterprise level enables greater standardisation, compliance, and operational excellence in regulated environments.

 

Generative AI and Large Language Models – Ken Molloy, SolutionsPT

Ken Molloy, Customer Success Manager at SolutionsPT, delivered an engaging session on Generative AI and Large Language Models, examining the rapid advancements reshaping today’s industrial landscape. Ken provided an in-depth look at how generative AI is already driving innovation, efficiency, and smarter automation across industries. He also highlighted how SolutionsPT supports organisations through comprehensive education, training, audits, consulting, and customer success management, empowering teams to adapt, evolve, and succeed with confidence.

 

Data in Sport – George Murray & Munster Rugby

George Murray, Lead Performance Analyst for Munster Rugby, shared fascinating insights into how data analysis supports high performance within elite sport. He was joined by Damien Falvey of Réalta Technologies to discuss Munster’s data-driven approach and how Réalta Technologies are helping coaches and players optimise performance, manage workloads, and gain competitive advantage, illustrating clear parallels between how data delivers value both on the pitch and in industry.

The event concluded with a panel discussion hosted by Barry Murphy, former Munster Rugby player, who was joined by Munster Rugby coaches and players to gain an insight into how they use data to improve their performance and find that extra 1% in competitive edge. 

 

A Collaborative Success

Réalta Technologies would like to extend sincere thanks to AVEVA and SolutionsPT for their sponsorship and support in making the day possible, to Munster Rugby for their hospitality and partnership, and to all who attended and contributed to such a successful event.

Finally, a special thanks to the Réalta Technologies team whose effort and expertise made the event a resounding success. A special thanks to Damien Falvey, Nikhil Ramisetty, Andreas Scannell, and Declan Hickey for representing Réalta on stage and sharing their expertise with the audience.

Réalta looks forward to hosting more events that bring together leaders across industry and sport to explore how data can unlock the next era of innovation and performance.

Turning Data into Action: Réalta Technologies Hosts Industry and Sport Event at Thomond Park

Turning Data into Action: Réalta Technologies Hosts Industry and Sport Event at Thomond Park Read More »

Realta Technologies Pi System Upgrade

PI System Upgrade Case Study for Pharmaceutical Manufacturing | Réalta Technologies

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PI System Upgrade Case Study for Pharmaceutical Manufacturing | Réalta Technologies

Introduction: 

Réalta Technologies recently completed a critical PI System upgrade for a leading pharmaceutical manufacturer. The project involved replacing ageing hardware and unsupported operating systems, ensuring the client’s data infrastructure met modern performance, security, and compliance standards. 

 

As a trusted partner and AVEVA Endorsed System Integrator, Réalta Technologies delivered a seamless transition to a fully upgraded system without data loss, enabling the client to continue operations without disruption and minimal downtime. 

 

The Challenge

The client’s PI System servers were operating on outdated hardware and operating systems. An upgrade-in-place was not possible due to:

  • Incompatibility with newer OS versions and software.
  • Requirement for new hardware to meet performance demands.
  • The need to keep existing servers intact for rollback in case of an issue.
  • The critical need to avoid any data loss during the transition.

These constraints required a carefully designed migration strategy that balanced operational continuity, data integrity, and validation requirements.

 

Possible Solutions

Drawing on extensive experience in industrial data infrastructure projects, Réalta Technologies identified three potential upgrade strategies:

 

Option 1: Adding New Servers to the PI Collective

  • Build new servers on new hardware and OS.
  • Add them to the existing PI System Collective.
  • Promote one of the new servers to Primary Data Archive.
  • Remove old servers once complete.

Pros: Minimal downtime, data available to users throughout.
Cons: Requires reconfiguring and restarting all interfaces, which can be time-consuming with large systems.

 

Option 2: Swapping Names and IP Addresses

  • Build new servers with temporary names.
  • Stop the PI Data Archives.
  • Swap the names/IP addresses with the old servers.
  • Restart PI Data Archives on the new hardware.

Pros: No interface reconfiguration required.
Cons: Brief downtime while archives are offline, though buffered data is restored.

 

Option 3: Building a Complete Parallel System

  • Create a fully independent system (Data Archive, AF, interface servers).
  • Restore a backup from the old system.
  • Run both systems in parallel until testing and validation are complete.

Pros: Safest approach, full validation before go-live, allows migration from Batch to Event Frames database in a controlled environment.
Cons: Requires more time, resources, and hardware.

 

Chosen Solution

After carefully reviewing all available upgrade paths, Réalta Technologies determined that Option 2: Swapping Names and IP Addresses was the most effective and efficient solution for this specific project.

 

This decision was based on our team’s in-depth understanding of both the technical requirements and the operational constraints within regulated pharmaceutical manufacturing. By applying our expertise in designing bespoke solutions, we were able to match the upgrade approach precisely to the client’s unique needs.

 

Several factors influenced our decision:

  • Minimising Disruption: The client’s PI System had multiple critical interfaces feeding data from across the site. Reconfiguring and restarting these, as required in other options, would have posed significant risk and extended downtime. Retaining the same names and IP addresses allowed us to transition to the new infrastructure seamlessly without altering the existing interface configuration.
  • Maintaining Operational Continuity: Pharmaceutical manufacturing operates under strict production and compliance demands. Swapping Names and IP Addresses enabled the upgrade to be completed within a tightly controlled maintenance window, avoiding unnecessary interruption to manufacturing activities.
  • Safeguarding Data Integrity: Our approach ensured that all data generated during the brief downtime was buffered and automatically restored to the upgraded system, protecting the accuracy and completeness of production records.
  • Bespoke Problem-Solving: Rather than applying a one-size-fits-all upgrade method, we evaluated the project holistically, balancing efficiency, safety, and compliance. Option 2 offered the best combination of speed, reliability, and risk mitigation for this particular environment.

This tailored solution is a clear example of how Réalta Technologies leverages its deep technical expertise and industry knowledge to deliver results that are both strategically sound and operationally safe, ensuring clients can modernise their systems without compromising productivity or compliance.

 

Benefits of Updating the PI System

  • Modern Infrastructure: New hardware and OS increased system performance and stability.
  • Data Integrity: All historical data retained with no loss during migration.
  • Reduced Operational Risk: Fully tested migration plan ensured predictable results.
  • Regulatory Compliance: Updated system aligned with industry best practices and supported ongoing GMP compliance.
  • Future-Ready Platform: Prepared for integration with advanced analytics, data visualisation tools, and machine learning applications.

 

Conclusion

This PI System upgrade demonstrated Réalta Technologies’ expertise in designing and executing complex data infrastructure projects for regulated industries. By selecting the optimal migration strategy and executing it flawlessly, Réalta ensured the client could continue delivering high-quality pharmaceutical products with minimal disruption.

 

As an AVEVA Endorsed System Integrator, Réalta Technologies provides tailored solutions that modernise industrial data systems while safeguarding compliance, security, and operational excellence.

 

Need help with updating your systems? Get in touch with our team.

Phone: +353 21 243 9113

Email: [email protected] 

PI System Upgrade Case Study for Pharmaceutical Manufacturing | Réalta Technologies

Introduction: 

Réalta Technologies recently completed a critical PI System upgrade for a leading pharmaceutical manufacturer. The project involved replacing ageing hardware and unsupported operating systems, ensuring the client’s data infrastructure met modern performance, security, and compliance standards. 

 

As a trusted partner and AVEVA Endorsed System Integrator, Réalta Technologies delivered a seamless transition to a fully upgraded system without data loss, enabling the client to continue operations without disruption and minimal downtime. 

 

The Challenge

The client’s PI System servers were operating on outdated hardware and operating systems. An upgrade-in-place was not possible due to:

  • Incompatibility with newer OS versions and software.
  • Requirement for new hardware to meet performance demands.
  • The need to keep existing servers intact for rollback in case of an issue.
  • The critical need to avoid any data loss during the transition.

These constraints required a carefully designed migration strategy that balanced operational continuity, data integrity, and validation requirements.

 

Possible Solutions

Drawing on extensive experience in industrial data infrastructure projects, Réalta Technologies identified three potential upgrade strategies:

 

Option 1: Adding New Servers to the PI Collective

  • Build new servers on new hardware and OS.
  • Add them to the existing PI System Collective.
  • Promote one of the new servers to Primary Data Archive.
  • Remove old servers once complete.

Pros: Minimal downtime, data available to users throughout.
Cons: Requires reconfiguring and restarting all interfaces, which can be time-consuming with large systems.

 

Option 2: Swapping Names and IP Addresses

  • Build new servers with temporary names.
  • Stop the PI Data Archives.
  • Swap the names/IP addresses with the old servers.
  • Restart PI Data Archives on the new hardware.

Pros: No interface reconfiguration required.
Cons: Brief downtime while archives are offline, though buffered data is restored.

 

Option 3: Building a Complete Parallel System

  • Create a fully independent system (Data Archive, AF, interface servers).
  • Restore a backup from the old system.
  • Run both systems in parallel until testing and validation are complete.

Pros: Safest approach, full validation before go-live, allows migration from Batch to Event Frames database in a controlled environment.
Cons: Requires more time, resources, and hardware.

 

Chosen Solution

After carefully reviewing all available upgrade paths, Réalta Technologies determined that Option 2: Swapping Names and IP Addresses was the most effective and efficient solution for this specific project.

 

This decision was based on our team’s in-depth understanding of both the technical requirements and the operational constraints within regulated pharmaceutical manufacturing. By applying our expertise in designing bespoke solutions, we were able to match the upgrade approach precisely to the client’s unique needs.

 

Several factors influenced our decision:

  • Minimising Disruption: The client’s PI System had multiple critical interfaces feeding data from across the site. Reconfiguring and restarting these, as required in other options, would have posed significant risk and extended downtime. Retaining the same names and IP addresses allowed us to transition to the new infrastructure seamlessly without altering the existing interface configuration.
  • Maintaining Operational Continuity: Pharmaceutical manufacturing operates under strict production and compliance demands. Swapping Names and IP Addresses enabled the upgrade to be completed within a tightly controlled maintenance window, avoiding unnecessary interruption to manufacturing activities.
  • Safeguarding Data Integrity: Our approach ensured that all data generated during the brief downtime was buffered and automatically restored to the upgraded system, protecting the accuracy and completeness of production records.
  • Bespoke Problem-Solving: Rather than applying a one-size-fits-all upgrade method, we evaluated the project holistically, balancing efficiency, safety, and compliance. Option 2 offered the best combination of speed, reliability, and risk mitigation for this particular environment.

This tailored solution is a clear example of how Réalta Technologies leverages its deep technical expertise and industry knowledge to deliver results that are both strategically sound and operationally safe, ensuring clients can modernise their systems without compromising productivity or compliance.

 

Benefits of Updating the PI System

  • Modern Infrastructure: New hardware and OS increased system performance and stability.
  • Data Integrity: All historical data retained with no loss during migration.
  • Reduced Operational Risk: Fully tested migration plan ensured predictable results.
  • Regulatory Compliance: Updated system aligned with industry best practices and supported ongoing GMP compliance.
  • Future-Ready Platform: Prepared for integration with advanced analytics, data visualisation tools, and machine learning applications.

 

Conclusion

This PI System upgrade demonstrated Réalta Technologies’ expertise in designing and executing complex data infrastructure projects for regulated industries. By selecting the optimal migration strategy and executing it flawlessly, Réalta ensured the client could continue delivering high-quality pharmaceutical products with minimal disruption.

 

As an AVEVA Endorsed System Integrator, Réalta Technologies provides tailored solutions that modernise industrial data systems while safeguarding compliance, security, and operational excellence.

 

Need help with updating your systems? Get in touch with our team.

Phone: +353 21 243 9113

Email: [email protected] 

PI System Upgrade Case Study for Pharmaceutical Manufacturing | Réalta Technologies Read More »

Power BI, Tableau, and SEEQ: Data Visualisation Tools for Modern Manufacturing

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Power BI, Tableau, and SEEQ: Data Visualisation Tools for Modern Manufacturing

Introduction: 

In the age of Industry 4.0, the volume of data generated in manufacturing environments continues to grow exponentially. But data alone doesn’t drive smarter decisions. It’s how you visualise and act on that data that creates real value. For companies in life sciences, pharmaceuticals, and high-volume manufacturing, choosing the right data visualisation tool is critical.

In this blog, we compare three leading tools in the space: Microsoft Power BI, Tableau, and SEEQ, examining their features, benefits, and use cases from the perspective of industrial data analytics.

 

Why Data Visualisation Matters in Manufacturing?

Before diving into the tools, it’s worth revisiting why data visualisation plays such a key role in manufacturing.

Manufacturers face constant pressure to increase yield, reduce downtime, improve compliance, and optimise performance. Data visualisation tools allow plant teams, analysts, and decision-makers to transform raw operational data into actionable insights. Whether tracking equipment efficiency or identifying production bottlenecks, the right dashboard can be the difference between reactive and proactive decision-making.

 

Power BI: Scalable, Accessible, and Microsoft-Native

Microsoft Power BI is one of the most widely used business intelligence platforms in the world. It offers deep integration with Microsoft products, scalability, and user-friendly interfaces, making it a powerful choice for companies already embedded in the Microsoft ecosystem.

 

Key Features:
  • Native integration with Excel, Azure, and SharePoint
  • Drag-and-drop dashboard creation
  • Custom DAX formulas for advanced metrics
  • Scheduled data refresh and real-time dashboards
  • Strong data modelling capabilities
Strengths:
  • Easy to adopt for teams already using Microsoft 365
  • Strong community support and regular updates
  • Affordable pricing tiers at enterprise level compared to other  visualization tools 
  • Suitable for both SME and enterprise scale
Manufacturing Use Cases:
  • OEE Dashboards: Track overall equipment effectiveness across multiple plants
  • Quality Monitoring: Monitor defect rates and identify trends
  • Supply Chain Analysis: Visualise logistics and inventory data
Limitations:
  • Can be less flexible for time-series industrial data
  • Requires additional configuration for integration with industrial historians like AVEVA PI or OSIsoft

Tableau: Powerful Visualisation and Data Exploration

Tableau is known for its visually rich dashboards and ability to handle large datasets from varied sources. It empowers users to explore data intuitively and supports custom, interactive reporting.

 

Key Features:
  • Rich data visualisation capabilities
  • Native support for many data connectors
  • Real-time data exploration and drill-downs
  • Customisable dashboards with dynamic filters
Strengths:
  • Intuitive UI for data analysts and non-technical users
  • Excellent at data storytelling and presenting complex trends
  • Highly flexible for different data sources and schemas
Manufacturing Use Cases:
  • Batch Performance Analysis: Track trends in batch processes over time
  • Energy Consumption Reporting: Visualise and compare energy usage across facilities
  • KPI Reporting Dashboards: Executive-level visual reporting across departments
Limitations:
  • Higher licensing costs than some alternatives
  • Not purpose-built for time-series industrial data
  • More suitable for data analysts than plant-floor users

SEEQ: Purpose-Built for Time-Series Industrial Data

SEEQ is designed specifically for advanced analytics in process manufacturing industries. Built to work with time-series data from historians like AVEVA PI or Canary, SEEQ enables engineers and analysts to gain insights from complex datasets quickly.

Key Features:
  • Native connectivity with AVEVA PI System, OSIsoft, and Canary
  • Purpose-built for time-series and event-based data
  • Predictive analytics and statistical modelling
  • Collaboration features for teams across functions
  • Strong integration with Jupyter for advanced data science
Strengths:
  • Ideal for engineers and process analysts
  • Handles large volumes of industrial data efficiently
  • Designed around manufacturing and life sciences workflows
  • Short time to value with minimal IT setup
Manufacturing Use Cases:
  • Process Optimisation: Identify trends and anomalies in production runs
  • Deviation Analysis: Investigate root causes of failures and off-spec product
  • Batch Comparisons: Compare equipment and material performance across runs
Limitations:
  • Not designed for traditional business metrics (e.g. finance or HR data)
  • Requires familiarity with process data structures and tag naming conventions

 

Choosing the Right Tool for Your Manufacturing Business

The best data visualisation tool depends on your organisation’s needs, data environment, and user base. Here’s a quick comparison:

Tool

Best For

Key Limitation

Power BI

Business dashboards and KPIs

Limited native support for time-series

Tableau

Visual storytelling and data exploration

Cost and complexity for industrial data

SEEQ

Advanced time-series analytics and manufacturing insights

Narrower business use cases

At Réalta Technologies, we work with clients to implement the right data visualisation solution based on their unique needs. This might be AVEVA PI paired with SEEQ for deep process insights, Tableau connected to AVEVA PI for advanced visual storytelling, or Power BI dashboards for plant-wide KPIs and reporting.

 

How Réalta Technologies Adds Value

As experts in industrial data architecture, data science, and automation, Réalta Technologies supports clients through every stage of their data journey. This includes infrastructure and historian setup, advanced analytics, and dashboard delivery.

We’ve successfully delivered SEEQ and AVEVA PI solutions across global manufacturing and life sciences clients. Our partnerships with leading technology providers and our in-house data engineering team ensure solutions that are tailored, validated, and built for real-world impact.

 

Conclusion

Data visualisation is not just about attractive dashboards. It’s about empowering teams with insights. Whether you need plant-level performance metrics, quality trends, or predictive insights, selecting the right visualisation tool is essential.

Power BI, Tableau, and SEEQ each offer distinct advantages. Understanding how they align with your infrastructure, team skillsets, and business goals helps ensure long-term value.

 

Need help selecting or implementing your data visualisation tools? Get in touch with our team.

 

Phone: +353 21 243 9113

Email: [email protected] 

Power BI, Tableau, and SEEQ: Data Visualisation Tools for Modern Manufacturing

Introduction: 

In the age of Industry 4.0, the volume of data generated in manufacturing environments continues to grow exponentially. But data alone doesn’t drive smarter decisions. It’s how you visualise and act on that data that creates real value. For companies in life sciences, pharmaceuticals, and high-volume manufacturing, choosing the right data visualisation tool is critical.

In this blog, we compare three leading tools in the space: Microsoft Power BI, Tableau, and SEEQ, examining their features, benefits, and use cases from the perspective of industrial data analytics.

 

Why Data Visualisation Matters in Manufacturing?

Before diving into the tools, it’s worth revisiting why data visualisation plays such a key role in manufacturing.

Manufacturers face constant pressure to increase yield, reduce downtime, improve compliance, and optimise performance. Data visualisation tools allow plant teams, analysts, and decision-makers to transform raw operational data into actionable insights. Whether tracking equipment efficiency or identifying production bottlenecks, the right dashboard can be the difference between reactive and proactive decision-making.

 

Power BI: Scalable, Accessible, and Microsoft-Native

Microsoft Power BI is one of the most widely used business intelligence platforms in the world. It offers deep integration with Microsoft products, scalability, and user-friendly interfaces, making it a powerful choice for companies already embedded in the Microsoft ecosystem.

 

Key Features:
  • Native integration with Excel, Azure, and SharePoint
  • Drag-and-drop dashboard creation
  • Custom DAX formulas for advanced metrics
  • Scheduled data refresh and real-time dashboards
  • Strong data modelling capabilities
Strengths:
  • Easy to adopt for teams already using Microsoft 365
  • Strong community support and regular updates
  • Affordable pricing tiers at enterprise level compared to other  visualization tools 
  • Suitable for both SME and enterprise scale
Manufacturing Use Cases:
  • OEE Dashboards: Track overall equipment effectiveness across multiple plants
  • Quality Monitoring: Monitor defect rates and identify trends
  • Supply Chain Analysis: Visualise logistics and inventory data
Limitations:
  • Can be less flexible for time-series industrial data
  • Requires additional configuration for integration with industrial historians like AVEVA PI or OSIsoft

Tableau: Powerful Visualisation and Data Exploration

Tableau is known for its visually rich dashboards and ability to handle large datasets from varied sources. It empowers users to explore data intuitively and supports custom, interactive reporting.

 

Key Features:
  • Rich data visualisation capabilities
  • Native support for many data connectors
  • Real-time data exploration and drill-downs
  • Customisable dashboards with dynamic filters
Strengths:
  • Intuitive UI for data analysts and non-technical users
  • Excellent at data storytelling and presenting complex trends
  • Highly flexible for different data sources and schemas
Manufacturing Use Cases:
  • Batch Performance Analysis: Track trends in batch processes over time
  • Energy Consumption Reporting: Visualise and compare energy usage across facilities
  • KPI Reporting Dashboards: Executive-level visual reporting across departments
Limitations:
  • Higher licensing costs than some alternatives
  • Not purpose-built for time-series industrial data
  • More suitable for data analysts than plant-floor users

SEEQ: Purpose-Built for Time-Series Industrial Data

SEEQ is designed specifically for advanced analytics in process manufacturing industries. Built to work with time-series data from historians like AVEVA PI or Canary, SEEQ enables engineers and analysts to gain insights from complex datasets quickly.

Key Features:
  • Native connectivity with AVEVA PI System, OSIsoft, and Canary
  • Purpose-built for time-series and event-based data
  • Predictive analytics and statistical modelling
  • Collaboration features for teams across functions
  • Strong integration with Jupyter for advanced data science
Strengths:
  • Ideal for engineers and process analysts
  • Handles large volumes of industrial data efficiently
  • Designed around manufacturing and life sciences workflows
  • Short time to value with minimal IT setup
Manufacturing Use Cases:
  • Process Optimisation: Identify trends and anomalies in production runs
  • Deviation Analysis: Investigate root causes of failures and off-spec product
  • Batch Comparisons: Compare equipment and material performance across runs
Limitations:
  • Not designed for traditional business metrics (e.g. finance or HR data)
  • Requires familiarity with process data structures and tag naming conventions

 

Choosing the Right Tool for Your Manufacturing Business

The best data visualisation tool depends on your organisation’s needs, data environment, and user base. Here’s a quick comparison:

Tool

Best For

Key Limitation

Power BI

Business dashboards and KPIs

Limited native support for time-series

Tableau

Visual storytelling and data exploration

Cost and complexity for industrial data

SEEQ

Advanced time-series analytics and manufacturing insights

Narrower business use cases

At Réalta Technologies, we work with clients to implement the right data visualisation solution based on their unique needs. This might be AVEVA PI paired with SEEQ for deep process insights, Tableau connected to AVEVA PI for advanced visual storytelling, or Power BI dashboards for plant-wide KPIs and reporting.

 

How Réalta Technologies Adds Value

As experts in industrial data architecture, data science, and automation, Réalta Technologies supports clients through every stage of their data journey. This includes infrastructure and historian setup, advanced analytics, and dashboard delivery.

We’ve successfully delivered SEEQ and AVEVA PI solutions across global manufacturing and life sciences clients. Our partnerships with leading technology providers and our in-house data engineering team ensure solutions that are tailored, validated, and built for real-world impact.

 

Conclusion

Data visualisation is not just about attractive dashboards. It’s about empowering teams with insights. Whether you need plant-level performance metrics, quality trends, or predictive insights, selecting the right visualisation tool is essential.

Power BI, Tableau, and SEEQ each offer distinct advantages. Understanding how they align with your infrastructure, team skillsets, and business goals helps ensure long-term value.

 

Need help selecting or implementing your data visualisation tools? Get in touch with our team.

 

Phone: +353 21 243 9113

Email: [email protected] 

Power BI, Tableau, and SEEQ: Data Visualisation Tools for Modern Manufacturing Read More »

What Is Databricks? A Modern Data Platform for Modern Businesses

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What Is Databricks? A Modern Data Platform for Modern Businesses

Introduction

Databricks is one of the most powerful and versatile platforms available for handling large-scale data analytics, machine learning, and AI workflows. Built on top of Apache Spark, it enables organisations to unify their data and AI strategies with scalable solutions tailored for speed, collaboration, and security.

As industries like life sciences, pharmaceutical manufacturing, and advanced engineering become increasingly data-rich, the need for a platform like Databricks becomes essential. At Réalta Technologies, we use Databricks to help clients unlock real-time insights, streamline operations, and make smarter, faster decisions.

What Is Databricks? 

Databricks is a cloud-based unified analytics platform designed to simplify the process of data engineering, data science, machine learning, and business intelligence. It brings together teams working with data into a single collaborative environment that supports the entire data lifecycle, from ingestion to modelling to visualisation.

It’s often described as a “lakehouse” platform, combining the best features of data lakes (scalability and flexibility) and data warehouses (structured querying and performance) in a single system.

 

 

Key Features of Databricks

 
1. Unified Workspace

Databricks enables data engineers, data scientists, and analysts to work in one collaborative environment. With shared notebooks, version control, and access management, the platform supports streamlined teamwork and knowledge sharing.

 

2. Delta Lake

Delta Lake is an open-source storage layer that brings ACID transaction capabilities to data lakes. This ensures reliability and consistency of data even as it scales.

 

3. Machine Learning & AI Integration

Databricks includes pre-built ML environments, AutoML tools, and native integrations with frameworks like TensorFlow, PyTorch, and XGBoost. This accelerates the development and deployment of machine learning models.

 

4. Optimised Apache Spark Engine

At its core, Databricks runs on Apache Spark, allowing it to process massive datasets quickly and efficiently across multiple nodes.

 

5. Scalability & Cloud Flexibility

Databricks supports multi-cloud environments and allows elastic scaling of compute resources, making it ideal for businesses with variable data workloads.

 

What Are the Benefits of Using Databricks?

Faster Time to Insight: Streamlined data pipelines and real-time processing enable teams to go from raw data to actionable insights faster.

Reduced Data Silos: By centralising your data, teams can eliminate fragmentation across departments and tools.

Improved Collaboration: A single platform for engineering, science, and analytics reduces duplication of work and fosters teamwork.

Scalability: Easily scale your workloads without overhauling infrastructure.

Cost Efficiency: With automated workflows and serverless options, Databricks helps reduce resource waste and manage costs effectively.

Security & Governance: Enterprise-grade controls for access, compliance, and data governance make it suitable for highly regulated industries.

 

Real-World Use Cases

Pharmaceutical Manufacturing

Databricks enables predictive maintenance, process optimisation, and batch analysis by aggregating data from lab systems, MES platforms, and IoT sensors. It supports compliance with regulations like 21 CFR Part 11 through robust audit trails and governance features.

 

Life Sciences R&D

Scientists and analysts can use Databricks to process large-scale genomic or clinical trial data, identify trends, and model outcomes using AI-driven methods.

 

Supply Chain Optimisation

With real-time analytics, Databricks helps monitor production rates, material availability, and logistics to support lean manufacturing strategies.

 

Predictive Quality Control

Machine learning models built in Databricks can detect early warning signs of quality deviations, allowing teams to act before products fall out of spec.

 

How Réalta Technologies Adds Value with Databricks

At Réalta Technologies, our data engineers and data scientists are experts in deploying Databricks to regulated environments. We work closely with clients in life sciences and manufacturing to:

  • Architect and implement secure, scalable Databricks environments.
  • Integrate data sources such as AVEVA PI, SCADA systems, MES, and LIMS.
  • Develop custom machine learning models for anomaly detection, predictive analytics, and process optimisation.
  • Maintain governance and compliance throughout the data lifecycle.
  • Train internal teams on best practices to make Databricks a sustainable part of their operations.

Our partnership with Databricks is a testament to the depth of experience our team brings in leveraging modern platforms to solve complex industrial challenges.

 

Conclusion

Databricks is transforming how industries harness the power of data. With its unified approach to engineering, science, and analytics, it supports innovation, efficiency, and growth at every stage of the data journey.

 

For organisations in regulated sectors, the ability to derive insights while maintaining control and compliance is essential. Réalta Technologies is proud to partner with clients to deliver intelligent, secure, and scalable solutions using Databricks.

 

Need help getting started with Databricks or optimising your existing deployment? Contact Réalta Technologies today:

Phone: +353 21 243 9113

Email: [email protected] 

 

What Is Databricks? A Modern Data Platform for Modern Businesses

Introduction

Databricks is one of the most powerful and versatile platforms available for handling large-scale data analytics, machine learning, and AI workflows. Built on top of Apache Spark, it enables organisations to unify their data and AI strategies with scalable solutions tailored for speed, collaboration, and security.

As industries like life sciences, pharmaceutical manufacturing, and advanced engineering become increasingly data-rich, the need for a platform like Databricks becomes essential. At Réalta Technologies, we use Databricks to help clients unlock real-time insights, streamline operations, and make smarter, faster decisions.

What Is Databricks? 

Databricks is a cloud-based unified analytics platform designed to simplify the process of data engineering, data science, machine learning, and business intelligence. It brings together teams working with data into a single collaborative environment that supports the entire data lifecycle, from ingestion to modelling to visualisation.

It’s often described as a “lakehouse” platform, combining the best features of data lakes (scalability and flexibility) and data warehouses (structured querying and performance) in a single system.

 

 

Key Features of Databricks

 
1. Unified Workspace

Databricks enables data engineers, data scientists, and analysts to work in one collaborative environment. With shared notebooks, version control, and access management, the platform supports streamlined teamwork and knowledge sharing.

 

2. Delta Lake

Delta Lake is an open-source storage layer that brings ACID transaction capabilities to data lakes. This ensures reliability and consistency of data even as it scales.

 

3. Machine Learning & AI Integration

Databricks includes pre-built ML environments, AutoML tools, and native integrations with frameworks like TensorFlow, PyTorch, and XGBoost. This accelerates the development and deployment of machine learning models.

 

4. Optimised Apache Spark Engine

At its core, Databricks runs on Apache Spark, allowing it to process massive datasets quickly and efficiently across multiple nodes.

 

5. Scalability & Cloud Flexibility

Databricks supports multi-cloud environments and allows elastic scaling of compute resources, making it ideal for businesses with variable data workloads.

 

What Are the Benefits of Using Databricks?

Faster Time to Insight: Streamlined data pipelines and real-time processing enable teams to go from raw data to actionable insights faster.

Reduced Data Silos: By centralising your data, teams can eliminate fragmentation across departments and tools.

Improved Collaboration: A single platform for engineering, science, and analytics reduces duplication of work and fosters teamwork.

Scalability: Easily scale your workloads without overhauling infrastructure.

Cost Efficiency: With automated workflows and serverless options, Databricks helps reduce resource waste and manage costs effectively.

Security & Governance: Enterprise-grade controls for access, compliance, and data governance make it suitable for highly regulated industries.

 

Real-World Use Cases

Pharmaceutical Manufacturing

Databricks enables predictive maintenance, process optimisation, and batch analysis by aggregating data from lab systems, MES platforms, and IoT sensors. It supports compliance with regulations like 21 CFR Part 11 through robust audit trails and governance features.

 

Life Sciences R&D

Scientists and analysts can use Databricks to process large-scale genomic or clinical trial data, identify trends, and model outcomes using AI-driven methods.

 

Supply Chain Optimisation

With real-time analytics, Databricks helps monitor production rates, material availability, and logistics to support lean manufacturing strategies.

 

Predictive Quality Control

Machine learning models built in Databricks can detect early warning signs of quality deviations, allowing teams to act before products fall out of spec.

 

How Réalta Technologies Adds Value with Databricks

At Réalta Technologies, our data engineers and data scientists are experts in deploying Databricks to regulated environments. We work closely with clients in life sciences and manufacturing to:

  • Architect and implement secure, scalable Databricks environments.
  • Integrate data sources such as AVEVA PI, SCADA systems, MES, and LIMS.
  • Develop custom machine learning models for anomaly detection, predictive analytics, and process optimisation.
  • Maintain governance and compliance throughout the data lifecycle.
  • Train internal teams on best practices to make Databricks a sustainable part of their operations.

Our partnership with Databricks is a testament to the depth of experience our team brings in leveraging modern platforms to solve complex industrial challenges.

 

Conclusion

Databricks is transforming how industries harness the power of data. With its unified approach to engineering, science, and analytics, it supports innovation, efficiency, and growth at every stage of the data journey.

 

For organisations in regulated sectors, the ability to derive insights while maintaining control and compliance is essential. Réalta Technologies is proud to partner with clients to deliver intelligent, secure, and scalable solutions using Databricks.

 

Need help getting started with Databricks or optimising your existing deployment? Contact Réalta Technologies today:

Phone: +353 21 243 9113

Email: [email protected] 

 

What Is Databricks? A Modern Data Platform for Modern Businesses Read More »

Unified Namespace (UNS)

What Is a Unified Namespace (UNS)? A Guide for Life Sciences and Manufacturing

Blog / By

What Is a Unified Namespace (UNS)? A Guide for Life Sciences and Manufacturing

Introduction

The life sciences and manufacturing industries are facing a common challenge: an overwhelming amount of data scattered across siloed systems, departments, and technologies. Whether it’s sensor readings from the production floor, batch records from MES systems, or operational insights from enterprise platforms, the information exists, but accessing it in a meaningful, unified way is often difficult.

 

This is where the concept of a Unified Namespace (UNS) comes in. While the term has gained visibility in recent years, the core principles behind UNS have existed for decades, with MQTT (Message Queuing Telemetry Transport) being the latest version. As digital transformation continues to shape regulated manufacturing, UNS is fast becoming the backbone of modern industrial data architecture, enabling real-time visibility, simplifying integration, and supporting data-driven decision-making.

Unified Namespace (UNS)

What Is a Unified Namespace?

A Unified Namespace (UNS) is a structured, centralised data layer that brings together real-time information from across an entire organisation  from machines and automation systems on the plant floor to business-level applications in the cloud. It acts as the single source of truth for industrial data, organised in a hierarchical format that mirrors the physical or logical structure of the business.


Unlike traditional architectures that rely on point-to-point integrations or static data lakes, a UNS operates in real-time using event-driven communication. When a change happens on the shop floor, that update is immediately reflected across all connected systems, users, and applications that subscribe to it.


Importantly, the UNS does not store data, it is a live data layer. It acts as the medium through which systems communicate, with data either passed on directly or sent to platforms that handle storage, such as historians or cloud-based analytics systems.


How a Unified Namespace Works

At the core of a UNS is a publish-subscribe model. Instead of pulling data from each system individually, each data source (e.g., a PLC or historian) publishes updates to a central broker. Any authorised system or user can then subscribe to the topics they need, ensuring they always have access to the most current information.


Common protocols used in a UNS include MQTT (Message Queuing Telemetry Transport). MQTT is the most up to date version the most commonly used protocol for implementing a UNS. It is lightweight, efficient, and designed for high-frequency data transmission. Paired with the Sparkplug B specification, MQTT can also handle structured payloads, device state tracking, and session awareness — making it ideal for industrial environments.


The data is typically organised in a logical hierarchy such as:
Enterprise > Site > Area > Line > Machine > Tag


This makes the data not only accessible but easily understandable to humans and machines alike.


Why UNS Matters in Life Sciences and Manufacturing

For life sciences and manufacturing companies, a UNS delivers clear advantages, particularly in environments where traceability, compliance, and timely decision-making are essential.


First, it eliminates data silos, bridging the gap between Operational Technology (OT) and Information Technology (IT). This allows manufacturing, quality, compliance, and business teams to work from a shared, real-time source of data.


Second, it improves data integrity and auditability, crucial in meeting GxP regulations and standards like 21 CFR Part 11 and Annex 11. With time-stamped, structured, and traceable records, regulatory inspections and investigations become far more manageable.


Third, a UNS empowers faster and more accurate decision-making by making the right data available to the right people, in the right format, at the right time, without manual intervention or custom integrations.


Technologies Commonly Used in a UNS

A number of platforms and tools can be used to implement a UNS. These typically fall into three categories: brokers, integration platforms, and data consumers.

 

MQTT Brokers

These act as the central hub where data is published and subscribed to. Popular options include:

  • HiveMQ – A high-performance MQTT broker with robust security and enterprise-grade reliability.
  • Cybus – Designed for industrial environments, Cybus Connectware offers data governance, role-based access control, and secure connectivity.
  • Ignition MQTT Engine (by Inductive Automation) – Frequently used in conjunction with Ignition SCADA, offering full support for Sparkplug B.
MQTT Data Integration Platforms

These platforms help bridge operational systems and higher-level applications, enriching and transforming data as it moves through the UNS.

  • HighByte Intelligence Hub – A powerful industrial data operations platform designed to model, integrate, and flow data in real time between OT and IT systems, supporting both UNS and broader data strategies.
Data Consumers

The UNS itself doesn’t store data — so it must work in tandem with systems that do. This includes:

  • Data historians (like AVEVA PI, Canary, or GE Proficy)
  • Analytics platforms (Power BI, Tableau, cloud services like Azure and AWS)
  • MES, SCADA, and ERP systems that rely on real-time data to manage operations

At Réalta Technologies, we design and implement Unified Namespace architectures using these platforms and more, based on the specific needs, infrastructure, and compliance requirements of each client.


As a newly appointed AVEVA Endorsed System Integrator, Réalta Technologies brings deep expertise in building UNS architectures that are not only technically robust but validated and scalable for regulated environments.

 

The Role of the Data Historian in a Unified Namespace

Although a UNS is not responsible for storing data, data historians play a critical role within this architecture.

A historian provides the long-term storage, analysis, and visualisation capabilities that the UNS layer alone cannot deliver. It collects time-stamped process data from the UNS (or directly from devices), enabling:

  • Batch review and traceability
  • Deviation investigations
  • Regulatory audit readiness
  • Trend analysis and predictive modelling

Platforms like AVEVA PI System, Canary, and GE Proficy Historian are often integrated with UNS architectures to provide robust historical records that complement the UNS’s real-time capabilities.


At Réalta Technologies, we work across these historian platforms, ensuring seamless integration with the UNS and alignment with compliance frameworks in GMP-regulated environments.

 

Key Benefits of Implementing a UNS

Implementing a UNS delivers measurable benefits, including:

  • Real-time, unified access to plant and enterprise data, improving cross-functional collaboration
  • Faster deployment of analytics and machine learning models, as data is structured and accessible
  • Streamlined integration between legacy equipment, modern platforms, and cloud tools
  • Greater agility and scalability, with an architecture that grows with the business
  • Stronger compliance through centralised audit trails and event logging

For companies working in life sciences or regulated manufacturing, the benefits are amplified. Unified access to clean, structured data can dramatically reduce batch review times, improve deviation investigations, and support continuous improvement initiatives, all while maintaining compliance.

 

Considerations for Getting Started

Before implementing a Unified Namespace, companies should consider a few key factors:

  • Current system landscape: Are your automation and IT systems capable of publishing and subscribing to real-time data?
  • Data governance: Who needs access to what data, and what controls are needed?
  • Validation requirements: How will the UNS be documented, qualified, and maintained to meet compliance standards?
  • Scalability: Can the architecture support multiple sites, product lines, or business units?
  • Partner support: Do you have access to integration specialists with experience in building secure, validated UNS environments?

At Réalta Technologies, we offer support from design through deployment, including validation documentation, user training, and long-term managed services.

 

Conclusion

A Unified Namespace is more than a technology trend, it’s a strategic foundation for the future of digital manufacturing. In the life sciences and manufacturing sectors, where the balance between agility, compliance, and performance is critical, a UNS offers a way to unify your data landscape and unlock new value from your systems.

 

By bringing together MQTT brokers, integration platforms like HighByte, and complementary systems like AVEVA PI, a UNS allows organisations to connect their data, and their teams, in a more intelligent way.

 

If you’re considering a Unified Namespace (UNS) or want to explore how it could support your digital strategy, we’re here to help.

Phone: +353 21 243 9113

Email: [email protected]

What Is a Unified Namespace (UNS)? A Guide for Life Sciences and Manufacturing

Introduction

The life sciences and manufacturing industries are facing a common challenge: an overwhelming amount of data scattered across siloed systems, departments, and technologies. Whether it’s sensor readings from the production floor, batch records from MES systems, or operational insights from enterprise platforms, the information exists, but accessing it in a meaningful, unified way is often difficult.

 

This is where the concept of a Unified Namespace (UNS) comes in. While the term has gained visibility in recent years, the core principles behind UNS have existed for decades, with MQTT (Message Queuing Telemetry Transport) being the latest version. As digital transformation continues to shape regulated manufacturing, UNS is fast becoming the backbone of modern industrial data architecture, enabling real-time visibility, simplifying integration, and supporting data-driven decision-making.

Unified Namespace (UNS)

What Is a Unified Namespace?

A Unified Namespace (UNS) is a structured, centralised data layer that brings together real-time information from across an entire organisation  from machines and automation systems on the plant floor to business-level applications in the cloud. It acts as the single source of truth for industrial data, organised in a hierarchical format that mirrors the physical or logical structure of the business.


Unlike traditional architectures that rely on point-to-point integrations or static data lakes, a UNS operates in real-time using event-driven communication. When a change happens on the shop floor, that update is immediately reflected across all connected systems, users, and applications that subscribe to it.


Importantly, the UNS does not store data, it is a live data layer. It acts as the medium through which systems communicate, with data either passed on directly or sent to platforms that handle storage, such as historians or cloud-based analytics systems.


How a Unified Namespace Works

At the core of a UNS is a publish-subscribe model. Instead of pulling data from each system individually, each data source (e.g., a PLC or historian) publishes updates to a central broker. Any authorised system or user can then subscribe to the topics they need, ensuring they always have access to the most current information.


Common protocols used in a UNS include MQTT (Message Queuing Telemetry Transport). MQTT is the most up to date version the most commonly used protocol for implementing a UNS. It is lightweight, efficient, and designed for high-frequency data transmission. Paired with the Sparkplug B specification, MQTT can also handle structured payloads, device state tracking, and session awareness — making it ideal for industrial environments.


The data is typically organised in a logical hierarchy such as:
Enterprise > Site > Area > Line > Machine > Tag


This makes the data not only accessible but easily understandable to humans and machines alike.


Why UNS Matters in Life Sciences and Manufacturing

For life sciences and manufacturing companies, a UNS delivers clear advantages, particularly in environments where traceability, compliance, and timely decision-making are essential.


First, it eliminates data silos, bridging the gap between Operational Technology (OT) and Information Technology (IT). This allows manufacturing, quality, compliance, and business teams to work from a shared, real-time source of data.


Second, it improves data integrity and auditability, crucial in meeting GxP regulations and standards like 21 CFR Part 11 and Annex 11. With time-stamped, structured, and traceable records, regulatory inspections and investigations become far more manageable.


Third, a UNS empowers faster and more accurate decision-making by making the right data available to the right people, in the right format, at the right time, without manual intervention or custom integrations.


Technologies Commonly Used in a UNS

A number of platforms and tools can be used to implement a UNS. These typically fall into three categories: brokers, integration platforms, and data consumers.

 

MQTT Brokers

These act as the central hub where data is published and subscribed to. Popular options include:

  • HiveMQ – A high-performance MQTT broker with robust security and enterprise-grade reliability.
  • Cybus – Designed for industrial environments, Cybus Connectware offers data governance, role-based access control, and secure connectivity.
  • Ignition MQTT Engine (by Inductive Automation) – Frequently used in conjunction with Ignition SCADA, offering full support for Sparkplug B.
MQTT Data Integration Platforms

These platforms help bridge operational systems and higher-level applications, enriching and transforming data as it moves through the UNS.

  • HighByte Intelligence Hub – A powerful industrial data operations platform designed to model, integrate, and flow data in real time between OT and IT systems, supporting both UNS and broader data strategies.
Data Consumers

The UNS itself doesn’t store data — so it must work in tandem with systems that do. This includes:

  • Data historians (like AVEVA PI, Canary, or GE Proficy)
  • Analytics platforms (Power BI, Tableau, cloud services like Azure and AWS)
  • MES, SCADA, and ERP systems that rely on real-time data to manage operations

At Réalta Technologies, we design and implement Unified Namespace architectures using these platforms and more, based on the specific needs, infrastructure, and compliance requirements of each client.


As a newly appointed AVEVA Endorsed System Integrator, Réalta Technologies brings deep expertise in building UNS architectures that are not only technically robust but validated and scalable for regulated environments.

 

The Role of the Data Historian in a Unified Namespace

Although a UNS is not responsible for storing data, data historians play a critical role within this architecture.

A historian provides the long-term storage, analysis, and visualisation capabilities that the UNS layer alone cannot deliver. It collects time-stamped process data from the UNS (or directly from devices), enabling:

  • Batch review and traceability
  • Deviation investigations
  • Regulatory audit readiness
  • Trend analysis and predictive modelling

Platforms like AVEVA PI System, Canary, and GE Proficy Historian are often integrated with UNS architectures to provide robust historical records that complement the UNS’s real-time capabilities.


At Réalta Technologies, we work across these historian platforms, ensuring seamless integration with the UNS and alignment with compliance frameworks in GMP-regulated environments.

 

Key Benefits of Implementing a UNS

Implementing a UNS delivers measurable benefits, including:

  • Real-time, unified access to plant and enterprise data, improving cross-functional collaboration
  • Faster deployment of analytics and machine learning models, as data is structured and accessible
  • Streamlined integration between legacy equipment, modern platforms, and cloud tools
  • Greater agility and scalability, with an architecture that grows with the business
  • Stronger compliance through centralised audit trails and event logging

For companies working in life sciences or regulated manufacturing, the benefits are amplified. Unified access to clean, structured data can dramatically reduce batch review times, improve deviation investigations, and support continuous improvement initiatives, all while maintaining compliance.

 

Considerations for Getting Started

Before implementing a Unified Namespace, companies should consider a few key factors:

  • Current system landscape: Are your automation and IT systems capable of publishing and subscribing to real-time data?
  • Data governance: Who needs access to what data, and what controls are needed?
  • Validation requirements: How will the UNS be documented, qualified, and maintained to meet compliance standards?
  • Scalability: Can the architecture support multiple sites, product lines, or business units?
  • Partner support: Do you have access to integration specialists with experience in building secure, validated UNS environments?

At Réalta Technologies, we offer support from design through deployment, including validation documentation, user training, and long-term managed services.

 

Conclusion

A Unified Namespace is more than a technology trend, it’s a strategic foundation for the future of digital manufacturing. In the life sciences and manufacturing sectors, where the balance between agility, compliance, and performance is critical, a UNS offers a way to unify your data landscape and unlock new value from your systems.

 

By bringing together MQTT brokers, integration platforms like HighByte, and complementary systems like AVEVA PI, a UNS allows organisations to connect their data, and their teams, in a more intelligent way.

 

If you’re considering a Unified Namespace (UNS) or want to explore how it could support your digital strategy, we’re here to help.

Phone: +353 21 243 9113

Email: [email protected]

What Is a Unified Namespace (UNS)? A Guide for Life Sciences and Manufacturing Read More »

Behind the Scenes: Réalta Technologies x Munster Rugby

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Behind the Scenes: Réalta Technologies x Munster Rugby

As proud Official Data Solutions Partners to Munster Rugby, we recently had the opportunity to spend a morning at the Munster Rugby High Performance Centre for a joint photoshoot. It was a great chance to capture some of the people and moments that represent this partnership — from the players and coaching staff to members of the Réalta Technologies team. 

Our work with Munster is built on shared values of performance, precision and continuous improvement, and we’re delighted to continue supporting the team both on and off the field.

You can view some of the shots from the day below.

Behind the Scenes: Réalta Technologies x Munster Rugby

As proud Official Data Solutions Partners to Munster Rugby, we recently had the opportunity to spend a morning at the Munster Rugby High Performance Centre for a joint photoshoot. It was a great chance to capture some of the people and moments that represent this partnership — from the players and coaching staff to members of the Réalta Technologies team. 

Our work with Munster is built on shared values of performance, precision and continuous improvement, and we’re delighted to continue supporting the team both on and off the field.

You can view some of the shots from the day below.

Behind the Scenes: Réalta Technologies x Munster Rugby Read More »

Understanding the Role of Different Data Historians in the Life Sciences Industry

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Understanding the Role of Different Data Historians in the Life Sciences Industry

Introduction

In the life sciences sector, data is a core asset. Whether it’s used for ensuring regulatory compliance, improving production efficiency, or supporting innovation, the ability to capture, store, and interpret operational data is fundamental. Data historians are central to this process. These specialised software systems are designed to collect, store and manage high-frequency, time-stamped data from manufacturing equipment, automation platforms, and control systems.

 

Unlike traditional databases, data historians are built specifically for handling time-series data, making them well-suited to the demands of regulated industries like pharmaceuticals, biotechnology, and medical device manufacturing. This article explores several of the most widely used data historian platforms in the life sciences industry, including AVEVA PI, Ignition, DeltaV, Canary, and GE Proficy, and how each supports robust data analytics and operational excellence.

AVEVA PI System 

The AVEVA PI System is one of the most established and widely adopted data historians across the life sciences industry. Known for its performance, scalability, and compliance-ready design, it is a preferred solution for global pharmaceutical and biotech companies. The PI System is capable of capturing real-time data from a wide range of equipment and systems, including SCADA, PLCs, and DCS networks. It stores this data in a structured and easily retrievable format, enabling everything from process monitoring to historical batch analysis. The PI System can also retrieve batch information from Batch Execution Systems and store it in its Event Frames database.

One of its major strengths lies in its ability to contextualise data through PI Asset Framework (AF), and present it using powerful visualisation tools such as PI Vision. These features support faster root cause analysis, better deviation management, and improved process visibility. Another key strength of AVEVA PI System is its openness. Data can be retrieved from a PI System using multiple third party applications SQL queries, OPC protocol or custom code etc…

For life sciences manufacturers operating under stringent regulatory requirements, PI provides native support for 21 CFR Part 11 and EU Annex 11, including electronic signatures, audit trails, and secure user access. Its reliability and accuracy make it a valuable asset for maintaining data integrity and ensuring audit readiness.

Réalta Technologies is proud to be an Endorsed System Integrator for AVEVA. This recognition represents the highest level of AVEVA partnership and is a direct reflection of Réalta’s technical expertise, proven delivery track record, and commitment to service excellence. As an Endorsed System Integrator, Réalta Technologies delivers customised PI solutions that help life sciences companies extract maximum value from their data infrastructure, ensuring that they meet compliance needs while unlocking opportunities for innovation.

 

Ignition 

Ignition is a modern industrial application platform that includes a capable and flexible data historian module. It is valued for its open architecture, modular design, and cost-effective licensing model, which allows organisations to scale deployments without incurring exponential costs.

Ignition collects real-time data from PLCs, sensors, and devices via standard industrial protocols, storing it in an SQL-based historian for easy access and integration. It offers comprehensive scripting capabilities, API access, and dashboard development tools, making it ideal for companies looking to build custom interfaces or analytics applications.

In the context of life sciences, Ignition is increasingly being used to manage data in single-site operations or specialised production lines. It supports integration with MES platforms and other enterprise systems, enabling a more holistic view of operations. When deployed correctly, it can meet compliance needs through secure data handling, access control, and reliable data retention policies. For companies focused on agility and innovation, Ignition offers a versatile and powerful alternative to traditional historians.

 

DeltaV Continuous Historian

The DeltaV Continuous Historian is an integral component of Emerson‘s DeltaV Distributed Control System, which is widely deployed in GMP-regulated environments. The historian is designed to store time-series data from process operations, making it highly suitable for both batch and continuous manufacturing in the life sciences sector.

Its tight integration with DeltaV control hardware and software ensures a seamless experience from data capture to analysis. It simplifies system validation and provides an audit-ready platform that helps meet 21 CFR Part 11 requirements. The historian can be configured to support electronic records and signatures, secure data storage, and change control protocols, all of which are critical in regulatory audits.

DeltaV Historian is commonly used in facilities where Emerson technologies form the core of the automation architecture. Its ability to deliver reliable, structured, and compliant data storage helps life sciences companies monitor production in real time, identify issues early, and continuously optimise performance.

 

Canary Historian

The Canary Historian is a lightweight, high-performance platform designed to handle fast, efficient data logging and visualisation. It is well-suited to life sciences organisations looking for a cost-effective, easy-to-deploy solution that still meets critical performance and compliance criteria.

Canary’s design prioritises data compression and high-speed throughput without compromising data integrity. It includes native trending tools and dashboard options, reducing the need for third-party analytics platforms. This makes it especially appealing for small to mid-sized facilities or teams seeking rapid time-to-value.

While not as widely adopted in enterprise life sciences environments as AVEVA PI or DeltaV, Canary is gaining traction due to its simplicity, speed, and ease of use. It can be configured to meet the needs of regulated environments with appropriate data security and retention configurations. Its integration capabilities also allow it to function alongside larger enterprise systems as a complementary or pilot solution.

 

GE Proficy Historian

GE Proficy Historian is a well-established industrial data platform used across various manufacturing sectors, including life sciences. It is designed for rapid deployment, secure data storage, and high-speed querying. Proficy Historian can be implemented as a standalone historian or as part of GE Digital’s wider Proficy suite, which includes analytics and MES functionality.

The platform supports data collection from multiple sources, including OPC, Modbus, and proprietary protocols. It is capable of handling both structured and unstructured data, making it suitable for capturing complex production data in a regulated environment. When configured appropriately, it can support compliance with regulatory standards for electronic records, access control, and data traceability.

In life sciences, GE Proficy is often deployed in facilities that require flexibility and fast implementation. Its user-friendly interface and strong security posture make it a good option for operations looking to improve data visibility without taking on the complexity of larger systems.

 

Choosing the Right Data Historian for Life Sciences

Choosing the right data historian is a strategic decision that depends on multiple factors, each shaped by the specific needs of the facility and the wider regulatory landscape. 

Regulatory Compliance

One of the most important considerations is regulatory compliance. Life sciences companies must meet stringent data integrity and traceability requirements, so it’s crucial to select a historian that natively supports 21 CFR Part 11 and Annex 11, including features like electronic signatures, audit trails, and secure access control.

Scalability & Integration

Scalability and integration are also key. Some facilities require an enterprise-wide solution capable of collecting and contextualising data across multiple production sites, while others may only need a site-specific platform that integrates seamlessly with existing SCADA, MES, and ERP systems. The historian should also be able to support long-term growth, allowing for additional users, higher data volumes, and future integration with analytics or cloud platforms.

Ease of Use

Another important factor is ease of deployment and validation. In GMP environments, the ability to validate systems quickly and efficiently can reduce risk and shorten timelines. Some platforms, like DeltaV Historian, are tightly integrated into control systems, which can simplify the validation process.

Costs

Cost and licensing flexibility are often overlooked but can have a major impact on long-term return on investment. Platforms like Ignition are known for their modular, unlimited licensing models, while others follow more traditional licensing structures. Each model comes with its own trade-offs in terms of scalability, support, and total cost of ownership.

Capabilities & Strategy

Finally, companies must consider their internal capabilities and long-term digital strategy. Some organisations prefer out-of-the-box solutions with minimal configuration, while others benefit from platforms that allow for greater customisation through scripting, APIs, or third-party integrations.

At Réalta Technologies, we work closely with life sciences clients to evaluate all these factors and select the best-fit historian for their needs. Our platform-agnostic approach and hands-on experience with systems like AVEVA PI, Ignition, DeltaV, Canary, and Proficy ensure that we can recommend solutions that align with both operational goals and regulatory obligations.

Conclusion

Data historians are foundational to modern life sciences manufacturing. From supporting real-time visibility to enabling detailed batch analysis, they underpin many of the industry’s critical functions. As regulatory expectations and digital transformation initiatives continue to evolve, having the right historian in place — and making full use of its capabilities — is essential.

Réalta Technologies partners with clients to design, deploy and optimise data historian solutions that deliver real value. Whether you are exploring new systems or looking to get more out of your current setup, we’re here to help you turn data into decisions.

Learn more about our solutions here: https://realtatechnologies.com/services/

Or contact us to discuss your challenges, and let us tailor a solution for you. 

Phone: +353 21 243 9113

Email: [email protected]

Understanding the Role of Different Data Historians in the Life Sciences Industry

Introduction

In the life sciences sector, data is a core asset. Whether it’s used for ensuring regulatory compliance, improving production efficiency, or supporting innovation, the ability to capture, store, and interpret operational data is fundamental. Data historians are central to this process. These specialised software systems are designed to collect, store and manage high-frequency, time-stamped data from manufacturing equipment, automation platforms, and control systems.

 

Unlike traditional databases, data historians are built specifically for handling time-series data, making them well-suited to the demands of regulated industries like pharmaceuticals, biotechnology, and medical device manufacturing. This article explores several of the most widely used data historian platforms in the life sciences industry, including AVEVA PI, Ignition, DeltaV, Canary, and GE Proficy, and how each supports robust data analytics and operational excellence.

AVEVA PI System 

The AVEVA PI System is one of the most established and widely adopted data historians across the life sciences industry. Known for its performance, scalability, and compliance-ready design, it is a preferred solution for global pharmaceutical and biotech companies. The PI System is capable of capturing real-time data from a wide range of equipment and systems, including SCADA, PLCs, and DCS networks. It stores this data in a structured and easily retrievable format, enabling everything from process monitoring to historical batch analysis. The PI System can also retrieve batch information from Batch Execution Systems and store it in its Event Frames database.

One of its major strengths lies in its ability to contextualise data through PI Asset Framework (AF), and present it using powerful visualisation tools such as PI Vision. These features support faster root cause analysis, better deviation management, and improved process visibility. Another key strength of AVEVA PI System is its openness. Data can be retrieved from a PI System using multiple third party applications SQL queries, OPC protocol or custom code etc…

For life sciences manufacturers operating under stringent regulatory requirements, PI provides native support for 21 CFR Part 11 and EU Annex 11, including electronic signatures, audit trails, and secure user access. Its reliability and accuracy make it a valuable asset for maintaining data integrity and ensuring audit readiness.

Réalta Technologies is proud to be an Endorsed System Integrator for AVEVA. This recognition represents the highest level of AVEVA partnership and is a direct reflection of Réalta’s technical expertise, proven delivery track record, and commitment to service excellence. As an Endorsed System Integrator, Réalta Technologies delivers customised PI solutions that help life sciences companies extract maximum value from their data infrastructure, ensuring that they meet compliance needs while unlocking opportunities for innovation.

 

Ignition 

Ignition is a modern industrial application platform that includes a capable and flexible data historian module. It is valued for its open architecture, modular design, and cost-effective licensing model, which allows organisations to scale deployments without incurring exponential costs.

Ignition collects real-time data from PLCs, sensors, and devices via standard industrial protocols, storing it in an SQL-based historian for easy access and integration. It offers comprehensive scripting capabilities, API access, and dashboard development tools, making it ideal for companies looking to build custom interfaces or analytics applications.

In the context of life sciences, Ignition is increasingly being used to manage data in single-site operations or specialised production lines. It supports integration with MES platforms and other enterprise systems, enabling a more holistic view of operations. When deployed correctly, it can meet compliance needs through secure data handling, access control, and reliable data retention policies. For companies focused on agility and innovation, Ignition offers a versatile and powerful alternative to traditional historians.

 

DeltaV Continuous Historian

The DeltaV Continuous Historian is an integral component of Emerson‘s DeltaV Distributed Control System, which is widely deployed in GMP-regulated environments. The historian is designed to store time-series data from process operations, making it highly suitable for both batch and continuous manufacturing in the life sciences sector.

Its tight integration with DeltaV control hardware and software ensures a seamless experience from data capture to analysis. It simplifies system validation and provides an audit-ready platform that helps meet 21 CFR Part 11 requirements. The historian can be configured to support electronic records and signatures, secure data storage, and change control protocols, all of which are critical in regulatory audits.

DeltaV Historian is commonly used in facilities where Emerson technologies form the core of the automation architecture. Its ability to deliver reliable, structured, and compliant data storage helps life sciences companies monitor production in real time, identify issues early, and continuously optimise performance.

 

Canary Historian

The Canary Historian is a lightweight, high-performance platform designed to handle fast, efficient data logging and visualisation. It is well-suited to life sciences organisations looking for a cost-effective, easy-to-deploy solution that still meets critical performance and compliance criteria.

Canary’s design prioritises data compression and high-speed throughput without compromising data integrity. It includes native trending tools and dashboard options, reducing the need for third-party analytics platforms. This makes it especially appealing for small to mid-sized facilities or teams seeking rapid time-to-value.

While not as widely adopted in enterprise life sciences environments as AVEVA PI or DeltaV, Canary is gaining traction due to its simplicity, speed, and ease of use. It can be configured to meet the needs of regulated environments with appropriate data security and retention configurations. Its integration capabilities also allow it to function alongside larger enterprise systems as a complementary or pilot solution.

 

GE Proficy Historian

GE Proficy Historian is a well-established industrial data platform used across various manufacturing sectors, including life sciences. It is designed for rapid deployment, secure data storage, and high-speed querying. Proficy Historian can be implemented as a standalone historian or as part of GE Digital’s wider Proficy suite, which includes analytics and MES functionality.

The platform supports data collection from multiple sources, including OPC, Modbus, and proprietary protocols. It is capable of handling both structured and unstructured data, making it suitable for capturing complex production data in a regulated environment. When configured appropriately, it can support compliance with regulatory standards for electronic records, access control, and data traceability.

In life sciences, GE Proficy is often deployed in facilities that require flexibility and fast implementation. Its user-friendly interface and strong security posture make it a good option for operations looking to improve data visibility without taking on the complexity of larger systems.

 

Choosing the Right Data Historian for Life Sciences

Choosing the right data historian is a strategic decision that depends on multiple factors, each shaped by the specific needs of the facility and the wider regulatory landscape. 

Regulatory Compliance

One of the most important considerations is regulatory compliance. Life sciences companies must meet stringent data integrity and traceability requirements, so it’s crucial to select a historian that natively supports 21 CFR Part 11 and Annex 11, including features like electronic signatures, audit trails, and secure access control.

Scalability & Integration

Scalability and integration are also key. Some facilities require an enterprise-wide solution capable of collecting and contextualising data across multiple production sites, while others may only need a site-specific platform that integrates seamlessly with existing SCADA, MES, and ERP systems. The historian should also be able to support long-term growth, allowing for additional users, higher data volumes, and future integration with analytics or cloud platforms.

Ease of Use

Another important factor is ease of deployment and validation. In GMP environments, the ability to validate systems quickly and efficiently can reduce risk and shorten timelines. Some platforms, like DeltaV Historian, are tightly integrated into control systems, which can simplify the validation process.

Costs

Cost and licensing flexibility are often overlooked but can have a major impact on long-term return on investment. Platforms like Ignition are known for their modular, unlimited licensing models, while others follow more traditional licensing structures. Each model comes with its own trade-offs in terms of scalability, support, and total cost of ownership.

Capabilities & Strategy

Finally, companies must consider their internal capabilities and long-term digital strategy. Some organisations prefer out-of-the-box solutions with minimal configuration, while others benefit from platforms that allow for greater customisation through scripting, APIs, or third-party integrations.

At Réalta Technologies, we work closely with life sciences clients to evaluate all these factors and select the best-fit historian for their needs. Our platform-agnostic approach and hands-on experience with systems like AVEVA PI, Ignition, DeltaV, Canary, and Proficy ensure that we can recommend solutions that align with both operational goals and regulatory obligations.

Conclusion

Data historians are foundational to modern life sciences manufacturing. From supporting real-time visibility to enabling detailed batch analysis, they underpin many of the industry’s critical functions. As regulatory expectations and digital transformation initiatives continue to evolve, having the right historian in place — and making full use of its capabilities — is essential.

Réalta Technologies partners with clients to design, deploy and optimise data historian solutions that deliver real value. Whether you are exploring new systems or looking to get more out of your current setup, we’re here to help you turn data into decisions.

Learn more about our solutions here: https://realtatechnologies.com/services/

Or contact us to discuss your challenges, and let us tailor a solution for you. 

Phone: +353 21 243 9113

Email: [email protected]

Understanding the Role of Different Data Historians in the Life Sciences Industry Read More »

Methods to Ensure Data Integrity in a Digitised Manufacturing Environment

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Methods to Ensure Data Integrity in a Digitised Manufacturing Environment

Introduction

Ensuring data integrity in manufacturing is essential for regulatory compliance, product quality, and operational efficiency. As the industry moves towards digitisation and automation, manufacturers must implement secure data management practices to meet the stringent requirements of FDA 21 CFR Part 11, GxP standards, and Good Manufacturing Practices (GMP).

With the rise of Industry 4.0, AI-driven analytics, and real-time data monitoring, organisations must adopt advanced data integrity solutions to prevent errors, eliminate data manipulation, and ensure compliance with global regulations.

This blog, written by industry experts at Realta Technologies, explores key strategies, best practices, and cutting-edge technologies to maintain data integrity in pharmaceutical, biotech, and industrial manufacturing environments.

 

What is Data Integrity in Manufacturing?

Data integrity refers to the accuracy, consistency, and reliability of electronic records throughout their lifecycle. It ensures that manufacturing data remains secure, unaltered, and audit-ready, minimising compliance risks.

In the pharmaceutical and biotech industries, data integrity aligns with ALCOA+ principles to ensure that data is:

  • Attributable – Clearly linked to the individual responsible for data entry.
  • Legible – Stored in a readable format that remains accessible over time.
  • Contemporaneous – Recorded in real-time without delays.
  • Original – Maintained in its raw, unaltered format.
  • Accurate – Free from errors, unauthorised changes, or falsifications.

Failure to maintain data integrity can result in FDA warning letters, regulatory fines, and product recalls, making compliance-critical industries highly dependent on robust data management systems.

Key Regulatory Requirements for Data Integrity

FDA 21 CFR Part 11 – Compliance for Electronic Records & Signatures

The FDA 21 CFR Part 11 regulation governs the use of electronic records and digital signatures in regulated industries. It requires:

  • Secure data storage with access controls.

  • Audit trails to track modifications.

  • Data validation to ensure authenticity and accuracy.

  • Electronic signatures for secure approvals and regulatory submissions.

GxP (Good x Practices) – Global Compliance Framework

GxP standards (such as GMP, GCP, and GDP) outline good manufacturing, clinical, and distribution practices to ensure product safety, efficacy, and quality. These require:

  • Validated systems for collecting, storing, and analysing data.

  • Change control policies to track modifications.

  • Audit-ready documentation for regulatory inspections.

Companies that fail to comply with these standards risk regulatory penalties, production halts, and damage to brand reputation.

 

Best Practices for Ensuring Data Integrity in Manufacturing

 

1. Implementing Secure and Validated Data Management Systems

To maintain compliance, manufacturers must use validated digital solutions to collect, process, and store data.

  • Data historians like AVEVA PI System ensure centralised, secure, and real-time data storage.

  • Manufacturing Execution Systems (MES) integration prevents manual data entry errors.

  • Access control protocols restrict unauthorised modifications.

Example: A pharmaceutical company using AVEVA PI to collect batch data ensures that only authorised personnel can modify or approve records, preventing data tampering.

 

2. Establishing Automated Audit Trails & Electronic Batch Records (EBRs)

Automated audit trails improve data transparency by tracking every modification in manufacturing and quality control systems.

  • Electronic batch records (EBRs) replace paper documentation, ensuring regulatory compliance.

  • Automated change logs help identify discrepancies in data entry.

  • Real-time alerts detect anomalies in production data.

Example: A biotech firm adopting Syncade MES for batch reporting uses automated exception tracking, allowing quality teams to focus only on critical deviations.

 

3. Connecting Standalone Systems to the Manufacturing OT Network

Many manufacturing environments still operate standalone, isolated systems that are not networked into the wider Operational Technology (OT) infrastructure. These islands of automation create data integrity risks due to manual processes, lack of backups, and limited security controls.

Integrating these standalone systems into an OT network significantly enhances data integrity, security, and compliance. Key advantages include:

  • User Management via Domain Active Directory and Windows Integrated Security

    • Standardised access control with centralised user authentication.

    • Reduces risks of unauthorised system modifications.

    • Improves regulatory compliance with secure login credentials.

  • Automated Data Collection

    • Eliminates manual data entry errors.

    • Ensures real-time tracking of critical manufacturing parameters.

    • Enhances reporting accuracy for regulatory audits.

  • Automated System Backups

    • Prevents data loss due to system failures or cyber threats.

    • Ensures data redundancy for compliance and business continuity.

  • Disaster Recovery and Business Continuity

    • Enables rapid recovery of manufacturing data in case of hardware failure or security breaches.

    • Ensures minimal downtime and regulatory compliance.

4. Integrating Digital Manufacturing Systems for Seamless Data Flow

To ensure complete traceability, manufacturers must integrate SCADA, MES, ERP, and IoT platforms for seamless data exchange.

  • OPC UA, MQTT, and BACNet protocols support real-time data transmission.

  • Cloud-based manufacturing solutions enable remote monitoring.

  • Automated data reconciliation minimises human intervention.

5. Training Employees on Data Security & Compliance

Regular training ensures that staff understand data security protocols and regulatory compliance requirements.

  • Quarterly compliance training sessions reinforce best practices.

  • Standard Operating Procedures (SOPs) outline data entry and validation processes.

  • Internal audits assess adherence to ALCOA+ principles.

Example: A biotech firm conducts quarterly data integrity training, reducing compliance errors by 30% over a year.

 

How Realta Technologies Helps You Ensure Data Integrity

At Realta Technologies, we specialise in implementing data integrity solutions tailored for pharma, biotech, and regulated manufacturing environments.

 

Our Expertise Includes:

  • AVEVA PI System & Data Historians – Secure storage and real-time access to process data.

  • MES & ERP Integrations – Seamless data flow between manufacturing systems.

  • Electronic Batch Records (EBRs) – Automated batch reporting with audit trails.

  • Data Analytics & Predictive Quality Control – Advanced monitoring using PowerBI & SEEQ.

  • Regulatory Compliance Support – Ensuring adherence to FDA 21 CFR Part 11 and GxP standards.

By working with Realta Technologies, manufacturers can ensure compliance, improve data security, and enhance operational efficiency.

Contact Realta Technologies today to discuss how we can help strengthen your data integrity strategy.

 

Conclusion

Data integrity is a critical factor in modern manufacturing, ensuring compliance with regulatory standards and improving product quality. By implementing secure digital systems, predictive analytics, and AI-driven automation, manufacturers can prevent compliance failures and data inconsistencies.

 

Realta Technologies provides the expertise, tools, and solutions required to establish audit-ready, high-integrity data systems for pharmaceutical, biotech, and industrial manufacturing sectors.

 

Learn more about our solutions here: https://realtatechnologies.com/services/

Ensure your manufacturing data meets the highest standards of integrity and compliance. Contact Réalta Technologies today for expert solutions that give you complete peace of mind in regulatory compliance and data security:

 

Phone: +353 21 243 9113

Email: [email protected]

Methods to Ensure Data Integrity in a Digitised Manufacturing Environment

Introduction

Ensuring data integrity in manufacturing is essential for regulatory compliance, product quality, and operational efficiency. As the industry moves towards digitisation and automation, manufacturers must implement secure data management practices to meet the stringent requirements of FDA 21 CFR Part 11, GxP standards, and Good Manufacturing Practices (GMP).

With the rise of Industry 4.0, AI-driven analytics, and real-time data monitoring, organisations must adopt advanced data integrity solutions to prevent errors, eliminate data manipulation, and ensure compliance with global regulations.

This blog, written by industry experts at Realta Technologies, explores key strategies, best practices, and cutting-edge technologies to maintain data integrity in pharmaceutical, biotech, and industrial manufacturing environments.

 

What is Data Integrity in Manufacturing?

Data integrity refers to the accuracy, consistency, and reliability of electronic records throughout their lifecycle. It ensures that manufacturing data remains secure, unaltered, and audit-ready, minimising compliance risks.

In the pharmaceutical and biotech industries, data integrity aligns with ALCOA+ principles to ensure that data is:

  • Attributable – Clearly linked to the individual responsible for data entry.
  • Legible – Stored in a readable format that remains accessible over time.
  • Contemporaneous – Recorded in real-time without delays.
  • Original – Maintained in its raw, unaltered format.
  • Accurate – Free from errors, unauthorised changes, or falsifications.

Failure to maintain data integrity can result in FDA warning letters, regulatory fines, and product recalls, making compliance-critical industries highly dependent on robust data management systems.

Key Regulatory Requirements for Data Integrity

FDA 21 CFR Part 11 – Compliance for Electronic Records & Signatures

The FDA 21 CFR Part 11 regulation governs the use of electronic records and digital signatures in regulated industries. It requires:

  • Secure data storage with access controls.

  • Audit trails to track modifications.

  • Data validation to ensure authenticity and accuracy.

  • Electronic signatures for secure approvals and regulatory submissions.

GxP (Good x Practices) – Global Compliance Framework

GxP standards (such as GMP, GCP, and GDP) outline good manufacturing, clinical, and distribution practices to ensure product safety, efficacy, and quality. These require:

  • Validated systems for collecting, storing, and analysing data.

  • Change control policies to track modifications.

  • Audit-ready documentation for regulatory inspections.

Companies that fail to comply with these standards risk regulatory penalties, production halts, and damage to brand reputation.

 

Best Practices for Ensuring Data Integrity in Manufacturing

 

1. Implementing Secure and Validated Data Management Systems

To maintain compliance, manufacturers must use validated digital solutions to collect, process, and store data.

  • Data historians like AVEVA PI System ensure centralised, secure, and real-time data storage.

  • Manufacturing Execution Systems (MES) integration prevents manual data entry errors.

  • Access control protocols restrict unauthorised modifications.

Example: A pharmaceutical company using AVEVA PI to collect batch data ensures that only authorised personnel can modify or approve records, preventing data tampering.

 

2. Establishing Automated Audit Trails & Electronic Batch Records (EBRs)

Automated audit trails improve data transparency by tracking every modification in manufacturing and quality control systems.

  • Electronic batch records (EBRs) replace paper documentation, ensuring regulatory compliance.

  • Automated change logs help identify discrepancies in data entry.

  • Real-time alerts detect anomalies in production data.

Example: A biotech firm adopting Syncade MES for batch reporting uses automated exception tracking, allowing quality teams to focus only on critical deviations.

 

3. Connecting Standalone Systems to the Manufacturing OT Network

Many manufacturing environments still operate standalone, isolated systems that are not networked into the wider Operational Technology (OT) infrastructure. These islands of automation create data integrity risks due to manual processes, lack of backups, and limited security controls.

Integrating these standalone systems into an OT network significantly enhances data integrity, security, and compliance. Key advantages include:

  • User Management via Domain Active Directory and Windows Integrated Security

    • Standardised access control with centralised user authentication.

    • Reduces risks of unauthorised system modifications.

    • Improves regulatory compliance with secure login credentials.

  • Automated Data Collection

    • Eliminates manual data entry errors.

    • Ensures real-time tracking of critical manufacturing parameters.

    • Enhances reporting accuracy for regulatory audits.

  • Automated System Backups

    • Prevents data loss due to system failures or cyber threats.

    • Ensures data redundancy for compliance and business continuity.

  • Disaster Recovery and Business Continuity

    • Enables rapid recovery of manufacturing data in case of hardware failure or security breaches.

    • Ensures minimal downtime and regulatory compliance.

4. Integrating Digital Manufacturing Systems for Seamless Data Flow

To ensure complete traceability, manufacturers must integrate SCADA, MES, ERP, and IoT platforms for seamless data exchange.

  • OPC UA, MQTT, and BACNet protocols support real-time data transmission.

  • Cloud-based manufacturing solutions enable remote monitoring.

  • Automated data reconciliation minimises human intervention.

5. Training Employees on Data Security & Compliance

Regular training ensures that staff understand data security protocols and regulatory compliance requirements.

  • Quarterly compliance training sessions reinforce best practices.

  • Standard Operating Procedures (SOPs) outline data entry and validation processes.

  • Internal audits assess adherence to ALCOA+ principles.

Example: A biotech firm conducts quarterly data integrity training, reducing compliance errors by 30% over a year.

 

How Realta Technologies Helps You Ensure Data Integrity

At Realta Technologies, we specialise in implementing data integrity solutions tailored for pharma, biotech, and regulated manufacturing environments.

 

Our Expertise Includes:

  • AVEVA PI System & Data Historians – Secure storage and real-time access to process data.

  • MES & ERP Integrations – Seamless data flow between manufacturing systems.

  • Electronic Batch Records (EBRs) – Automated batch reporting with audit trails.

  • Data Analytics & Predictive Quality Control – Advanced monitoring using PowerBI & SEEQ.

  • Regulatory Compliance Support – Ensuring adherence to FDA 21 CFR Part 11 and GxP standards.

By working with Realta Technologies, manufacturers can ensure compliance, improve data security, and enhance operational efficiency.

Contact Realta Technologies today to discuss how we can help strengthen your data integrity strategy.

 

Conclusion

Data integrity is a critical factor in modern manufacturing, ensuring compliance with regulatory standards and improving product quality. By implementing secure digital systems, predictive analytics, and AI-driven automation, manufacturers can prevent compliance failures and data inconsistencies.

 

Realta Technologies provides the expertise, tools, and solutions required to establish audit-ready, high-integrity data systems for pharmaceutical, biotech, and industrial manufacturing sectors.

 

Learn more about our solutions here: https://realtatechnologies.com/services/

Ensure your manufacturing data meets the highest standards of integrity and compliance. Contact Réalta Technologies today for expert solutions that give you complete peace of mind in regulatory compliance and data security:

 

Phone: +353 21 243 9113

Email: [email protected]

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