As 2025 comes to a close, the data analytics landscape continues to evolve at a pace few industries can match. What was once centred on historical reporting and isolated datasets has matured into a connected, intelligent ecosystem that influences decision-making in real time. For organisations across life sciences, pharmaceuticals, manufacturing, energy and utilities, data is no longer a by-product of operations. It is a strategic asset.

Looking ahead to 2026 and beyond, several clear trends are emerging that will shape how organisations collect, manage, analyse and act on data. These developments are not about adopting the latest technology for its own sake. They are about building resilience, maintaining compliance, improving efficiency and enabling smarter decisions across increasingly complex operations.

From Data Collection to Data Intelligence

One of the most significant shifts underway is the move from basic data collection towards true data intelligence. Many organisations have already invested heavily in historians, automation systems and reporting platforms. The challenge now is not access to data, but the ability to contextualise it, trust it and extract meaningful insight from it.

By 2026, successful organisations will be those that have moved beyond disconnected data sources and created well-structured, governed data foundations. This includes consistent naming standards, clear ownership, strong data integrity practices and alignment with operational models such as ISA-95. Without this groundwork, advanced analytics and AI initiatives struggle to deliver value.

Artificial Intelligence Becomes Operational, Not Experimental

Artificial Intelligence has dominated recent industry conversations, but its role is now shifting from experimentation to practical, operational use. In regulated industries especially, AI adoption has been cautious, and rightly so. However, we are now seeing a clear move towards AI solutions that are explainable, auditable and aligned with regulatory expectations.

In the years ahead, AI will increasingly be embedded into everyday operational workflows. This includes predictive maintenance, anomaly detection, quality monitoring, demand forecasting and decision support. Rather than replacing human expertise, AI will augment it, enabling engineers, operators and analysts to focus on higher-value tasks while routine analysis runs continuously in the background.

Importantly, organisations will place greater emphasis on trustworthy AI. This means models built on high-quality data, transparent logic and robust validation, particularly in life sciences and pharmaceutical manufacturing where patient safety and compliance are paramount.

Real-Time Insight Becomes the Standard

The expectation of real-time or near-real-time insight is becoming the norm rather than the exception. Operational teams increasingly expect to understand what is happening now, not what happened last week. Advances in data infrastructure, streaming technologies and modern visualisation platforms are making this possible at scale.

By 2026, real-time dashboards, alerts and analytics will be embedded across operations, from shop floor monitoring to executive decision-making. This shift supports faster response times, improved operational agility and reduced downtime. It also places greater responsibility on organisations to ensure that real-time data is accurate, contextualised and governed correctly.

Greater Focus on Data Architecture and Interoperability

As technology ecosystems become more complex, the importance of strong data architecture continues to grow. Organisations are increasingly recognising that long-term success depends on systems that can evolve without repeated large-scale rework.

Future-ready data strategies will prioritise interoperability between systems, vendors and platforms. This includes automation systems, data historians, analytics tools and enterprise applications working together seamlessly. Open standards, scalable architectures and flexible integration approaches will be key enablers of this trend.

Analytics Moves Closer to the Business

Another notable trend is the continued democratisation of data analytics. While deep technical expertise remains essential behind the scenes, analytics tools are becoming more accessible to a wider range of users. Engineers, quality teams and operations managers increasingly expect self-service access to insights without needing to rely on specialist teams for every request.

This does not reduce the need for expert data professionals. On the contrary, it increases the importance of well-designed solutions that balance usability with governance, ensuring that insights are reliable, secure and compliant.

Compliance and Data Integrity Remain Non-Negotiable

In regulated industries, compliance and data integrity will continue to underpin every data initiative. As analytics and AI capabilities expand, regulators will expect the same level of control, traceability and validation as traditional systems.

Looking ahead, organisations that successfully integrate compliance into their digital strategies from the outset will be best positioned to innovate with confidence. This includes validation-aware system design, strong change management processes and continuous monitoring of data quality.

Preparing for the Future

The future of data analytics is not defined by a single technology or trend. It is shaped by how organisations bring together people, processes and platforms to create sustainable, value-driven solutions. The most successful organisations will be those that invest in strong foundations, adopt emerging technologies pragmatically and partner with experts who understand both the technical and regulatory landscapes.

As we move into 2026 and beyond, data analytics will continue to play a central role in operational excellence, innovation and competitive advantage. The opportunity is significant, but so is the responsibility to implement these capabilities thoughtfully and effectively.

To learn more about how Réalta Technologies can help you excel in 2026, contact us on;

sales@realtatechnologies.com
https://realtatechnologies.com
IRL: +353 21 243 9113 | US: +1 302 509 4401

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.

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:

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: sales@Realtatechnologies.com 

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.

Introduction

The industrial world is rapidly evolving, and businesses need efficient, scalable, and secure solutions to manage their vast amounts of operational data. AVEVA Connect is one of the most powerful cloud-based platforms for industrial data management, offering a unified solution for integrating, analysing, and visualising data across an enterprise.

By enabling seamless data access, collaboration, and analytics, AVEVA Connect empowers companies to optimise their operations and accelerate their digital transformation efforts.

In this blog, we will explore:
1. What AVEVA Connect is and how it works
2. Key benefits of using AVEVA Connect
3. Example use cases across industries
4. How Realta Technologies can help businesses leverage AVEVA Connect for better data management and efficiency.

What is AVEVA Connect?

AVEVA Connect is a cloud-based industrial platform that enables organisations to store, integrate, and analyse data from multiple sources in one centralised system. It is designed to help manufacturers, energy companies, and industrial enterprises make data-driven decisions by providing real-time visibility and collaboration across teams.

How It Works;

AVEVA Connect acts as a digital hub, allowing businesses to:

• Securely store and access operational and historical data from anywhere.
• Integrate multiple data sources such as SCADA, PLCs, IoT devices, and enterprise systems.
• Analyse and visualise data with powerful analytics tools.
• Enhance collaboration by enabling teams to access and share data in real time.

AVEVA Connect supports various AVEVA applications such as AVEVA PI System, AVEVA Insight, and AVEVA Edge, making it a flexible and scalable cloud solution for industrial businesses.

Introduction

In today’s data-driven world, organisations rely on three crucial roles to extract valuable insights from the vast amounts of data they generate: Data Engineers, Data Scientists, and Data Analysts. While each role serves a distinct purpose, there are key areas where their responsibilities overlap, enabling seamless integration and insight generation. 

This blog explores the differences between these roles and how Réalta Technologies offers a comprehensive range of services that covers all three.

What Does a Data Engineer Do?

Data Engineers are responsible for creating the infrastructure that enables data collection, storage, and processing. Their primary focus is to ensure that data is available, organised, and ready for further analysis by building robust data pipelines and managing databases.

Key Responsibilities:

• Data Architecture: Designing and structuring the framework for data storage and accessibility.
• Infrastructure Setup: Implementing systems to capture and process real-time data.
• Database Management: Overseeing data storage, ensuring its organisation, and handling large datasets efficiently.
• Scalability Solutions: Building systems that can scale with growing data needs.

At Réalta Technologies, Data Engineers specialise in automating connectivity and ensuring smooth data flow using communication protocols like OPC DA, OPC UA, MQTT, BACNet, and various fieldbus communications.

What Does a Data Scientist Do?

A Data Scientist focuses on analysing and interpreting complex datasets to generate actionable insights. They apply advanced machine learning models and algorithms to predict future outcomes, optimise processes, and solve business problems. Their work relies heavily on the infrastructure built by Data Engineers.

Key Responsibilities:

• Machine Learning & Predictive Modeling: Applying algorithms to make data-driven predictions.
• Statistical Analysis: Analysing large datasets to identify trends, correlations, and outliers.
• Algorithm Optimisation: Continuously improving models to enhance their accuracy.
• Data Cleaning & Preparation: Ensuring data quality and preparing it for analysis.

At Réalta Technologies, Data Scientists utilise tools like AVEVA PI, Ignition, and SEEQ to create advanced models that help businesses optimise their processes and improve decision-making.

What Does a Data Analyst Do?

Data Analysts focus on making sense of the data by translating complex findings into clear, actionable insights. They interpret data, create reports, and visualise trends, ensuring that stakeholders can use the data effectively for strategic decisions.

Key Responsibilities:

• Data Querying & Analysis: Extracting specific datasets and interpreting them to uncover meaningful patterns.
• Insight Generation: Turning raw data into actionable insights for business stakeholders.
• KPI Tracking & Performance Benchmarking: Monitoring key performance indicators to track progress.
• Reporting & Visualisation: Using tools to create automated reports and dashboards for easy data interpretation.

Réalta Technologies’ Data Analysts rely on platforms like PowerBI and Tableau to provide comprehensive, interactive dashboards that allow businesses to monitor performance metrics in real time.

Where Do These Roles Overlap?

While the roles of Data Engineers, Data Scientists, and Data Analysts are distinct, they do overlap in important areas:

Integration (Data Engineer + Data Scientist)

Data Engineers and Data Scientists work closely together to ensure that data pipelines are optimised for analysis. Data Engineers provide clean, well-organised datasets, while Data Scientists use these datasets to build and refine models. Together, they focus on:

• Pipeline Optimisation: Ensuring efficient data flow for real-time analysis.
• Data Cleaning Automation: Automating the process of preparing raw data for analysis.
• Real-Time Data Processing: Creating systems that allow for live monitoring and data-based decision-making.

Insights (Data Scientist + Data Analyst)

Data Scientists and Data Analysts overlap in their work of interpreting and analysing data. Data Scientists build models and algorithms, while Data Analysts use these models to generate insights and actionable reports. Together, they focus on:

• Data Querying: Extracting relevant datasets for further analysis.
• Insight Generation: Collaborating to turn analytical results into understandable insights.
• Advanced Data Analysis: Combining machine learning models with business-oriented reporting.

How Réalta Technologies Delivers All Three Services

At Réalta Technologies, we offer a comprehensive range of services that cover all three key roles: Data Engineers, Data Scientists, and Data Analysts. By delivering these services in an integrated manner, we provide businesses with the tools they need to collect, process, and understand their data.

Our Expertise Includes:

• Data Engineering: We design and implement robust data pipelines and infrastructure to ensure your data is always accessible and ready for analysis.
• Data Science: We apply advanced machine learning and statistical techniques to analyse your data and make predictive insights that drive informed decision-making.
• Data Analytics: Our analysts create customised reports and dashboards using tools like PowerBI and Tableau, turning raw data into actionable insights that you can use to improve performance.

Tools We Use:

We rely on a variety of industry-leading tools and platforms to deliver the best possible solutions for your business:

• AVEVA PI, Ignition, SEEQ: For real-time data processing and analysis.
• PowerBI, Tableau: For intuitive reporting and data visualisation that offers comprehensive insights at a glance.

Conclusion

The data lifecycle is complex, and it requires a collaborative effort between Data Engineers, Data Scientists, and Data Analysts to derive maximum value from the data generated by businesses. At Réalta Technologies, we combine these three essential roles to deliver holistic data solutions. From capturing and processing data to generating actionable insights, our experts are here to help you leverage your data for better decision-making, optimised processes, and improved business outcomes.

Contact Réalta Technologies today to learn how we can help you build an integrated data strategy that covers everything from infrastructure to insight generation.

Phone: +353 21 243 9113

Email: sales@realtatechnologies.com

Introduction

Sustainability has become a central focus for industries worldwide, and manufacturing is no exception. With the increasing demand for eco-friendly practices, companies are under pressure to reduce their environmental impact while maintaining efficient operations. One of the most significant challenges in achieving this balance is energy usage, a critical component of both operational costs and sustainability metrics. In this post, we will explore the role of data capture, analysis, and reporting in promoting sustainability in manufacturing and how Réalta Technologies is helping businesses achieve their sustainability goals.

The Energy Challenge in Manufacturing

Manufacturing facilities are energy-intensive by nature, with operations that require large amounts of electricity, gas, and other resources. Energy consumption can account for a substantial portion of a facility’s operational expenses, and inefficient energy use not only impacts the bottom line but also increases the environmental footprint. For companies striving to meet sustainability targets, understanding and optimising energy usage is key.

In recent years, there has been a growing demand for manufacturers to track and report sustainability metrics, such as carbon emissions, water usage, and overall energy consumption. However, the challenge for many facilities lies in the lack of visibility into how energy is used across various operations. Without accurate data, it is difficult to pinpoint areas where energy efficiency can be improved or determine the effectiveness of sustainability initiatives.

The Role of Automation and Data Capture in Sustainability

Réalta Technologies understands the complexities of energy management in manufacturing and offers cutting-edge solutions to help facilities better understand their energy usage. Through automation connectivity and advanced data analytics, manufacturers can gain comprehensive visibility into their operations, allowing them to make data-driven decisions that support sustainability.

Key Benefits of Réalta Technologies’ Data Capture Solutions:

• Automation Connectivity: Réalta Technologies specialises in connecting industrial systems to capture real-time data from various equipment and processes. Using a range of industrial communication protocols such as OPC DA, OPC UA, MQTT, BACNet, and various fieldbus communications, we enable seamless integration across multiple systems and devices, ensuring no data is left behind.
• Data Analysis and Reporting: Once data is captured, Réalta Technologies provides advanced reporting and analytics tools that allow manufacturing sites to break down their energy consumption. This helps facilities determine critical insights, such as energy usage during production vs. non-production times. For instance, a manufacturer can analyse how much energy is consumed during a batch process compared to when equipment is idle, helping to uncover opportunities for energy savings.

Using Data to Optimise Facility Sustainability

The journey towards sustainability begins with understanding how resources are being used. With the right data in hand, manufacturers can take a strategic approach to reducing their energy consumption, improving efficiency, and minimising their environmental footprint.

1. Energy Consumption Patterns

Réalta Technologies enables manufacturers to identify trends in energy consumption by collecting real-time data across all production stages. By comparing energy use during batch runs versus downtime, facilities can pinpoint inefficiencies, such as idle equipment consuming unnecessary power. This type of analysis allows companies to implement targeted energy-saving measures, such as shutting down non-essential equipment during off-peak hours or optimising heating, ventilation, and air conditioning (HVAC) systems to reduce energy waste.

2. Benchmarking for Sustainability

By tracking sustainability metrics over time, manufacturers can measure the impact of their energy optimisation strategies and set realistic goals for improvement. Réalta Technologies’ data reporting tools help companies benchmark their performance, ensuring they meet or exceed sustainability targets. Through continuous monitoring and reporting, facilities can identify areas where additional improvements can be made, contributing to long-term sustainability.

3. Carbon Emission Reduction

Energy usage is closely tied to carbon emissions, and reducing energy consumption is a direct way to lower a facility’s carbon footprint. With Réalta Technologies’ solutions, manufacturers can generate detailed reports on energy usage and its associated carbon emissions. These reports can then be used to develop strategies for further reducing emissions, helping companies meet regulatory requirements and align with corporate sustainability goals.

The Tools Behind Réalta Technologies’ Solutions

Réalta Technologies partners with industry-leading applications to provide manufacturers with the best-in-class tools for data collection, analysis, and reporting. These include:

• AVEVA PI: A powerful data infrastructure that captures and stores real-time data from industrial processes, offering deep insights into energy usage and operational efficiency.
• Ignition: An industrial automation platform that seamlessly connects devices and data across the facility, allowing manufacturers to monitor and optimise their systems in real-time.
• SEEQ: An advanced analytics platform designed to help manufacturers analyse large volumes of data and identify trends and anomalies, essential for optimising energy consumption.
• PowerBI: A business analytics tool that enables the creation of interactive reports and dashboards, helping stakeholders visualise energy data and make informed decisions.
• Tableau: Another powerful data visualisation tool, Tableau helps manufacturers turn raw data into actionable insights, making it easier to track sustainability metrics and energy usage trends.

How Réalta Technologies Drives Sustainability

At Réalta Technologies, we believe that data is the key to unlocking sustainability in manufacturing. By providing manufacturers with the tools and expertise to capture, analyse, and report on energy usage, we empower businesses to take control of their sustainability goals. Whether it’s through automation connectivity or advanced analytics, our solutions help manufacturers:

• Gain visibility into energy consumption across all operations
• Identify inefficiencies and opportunities for energy optimisation
• Track sustainability metrics and monitor progress over time
• Reduce carbon emissions and meet environmental regulations

Conclusion

Sustainability is no longer an option for manufacturers—it’s a necessity. As the world shifts towards more eco-friendly practices, companies that prioritise energy efficiency and resource optimisation will lead the way in reducing environmental impact. Réalta Technologies is committed to helping manufacturers achieve their sustainability goals through data-driven solutions. By leveraging our expertise in automation and data analytics, manufacturing sites can gain the insights needed to optimise energy use, reduce costs, and improve their overall environmental footprint.

Contact Us

Ready to optimise your facility’s sustainability efforts? Contact Réalta Technologies today to learn how our data capture and reporting solutions can help you achieve your energy efficiency and sustainability goals.

https://realtatechnologies.com/contact/

sales@realtatechnologies.com

+353 (0)21 2439113

Introduction

In the rapidly evolving pharmaceutical industry, the need for real-time data collection, analysis, and visualisation have become crucial for maintaining operational efficiency and compliance. Réalta Technologies has demonstrated its expertise in this domain by successfully implementing a High-Availability PI System at a BioPharma site specialising in Fill Finish operations. 

This case study is one example of many full PI System implementations we have completed this year and highlights the advanced systems and technologies integrated by Réalta Technologies and the significant benefits they bring to the site.

Understanding the Customer’s Requirements

The BioPharma site required a robust and reliable system capable of collecting, storing, analysing, and visualising both real-time and historical operational data from various critical areas within the facility. These areas included the Formulations Suite, Component Preparation, Filling & Inspection, Labs, Clean and Black Utilities, and the Building Management System (BMS). The primary objective was to implement a High-Availability PI System that could integrate seamlessly with existing systems and provide comprehensive insights into operational performance.

Systems Integrated

Réalta Technologies expertly integrated a range of systems to achieve the desired outcomes for the BioPharma site:

• • DeltaV Batch System: Facilitates precise control and monitoring of batch processes, ensuring consistency and quality in production.
  • Syncade MES: Provides Manufacturing Execution System (MES) capabilities, enhancing production management and compliance.
  • Siemens & Allen Bradley PLC’s and HMI’s: Critical for controlling and monitoring automated processes and equipment across the site.
  • Desigo BMS: Manages building systems such as HVAC, lighting, and security to ensure a controlled environment.
  • LIMS (Laboratory Information Management System): Streamlines lab operations by managing samples, associated data, and laboratory workflows, ensuring data integrity and compliance.

Technologies Deployed

To meet the complex requirements of the BioPharma site, Réalta Technologies employed a suite of advanced technologies that work in tandem to deliver real-time insights and analytics:

• PI Data Archive: Redundant central repository for all operational data, ensuring secure and efficient data storage.
• PI Asset Framework (AF): Provides a contextualised representation of data, enabling users to easily navigate and analyse information.
• MS SQL Server: Allows redundancy and robust support for the databases used for the PI system’s Metadata
• PI Analytics: Allows for the creation of sophisticated analytics models, providing actionable insights from the collected data.
• PI Vision & Datalink: Facilitates intuitive data visualisation and interaction through dashboards and reporting tools.
• PI Event Frames Generator (EFGen): Generates event frames for tracking process events and exceptions, crucial for batch reporting.
• PI Notifications: Automates alerts and notifications, ensuring timely response to critical conditions.
• RtReports: Enables comprehensive reporting and review by exception, streamlining compliance and quality assurance processes.
• PI Integrator for Business Analytics: Integrates PI System data with business intelligence tools, enhancing strategic decision-making.
• PI WebAPI: Provides programmatic access to PI System data, enabling custom applications and integrations.
• Python: Utilised for developing custom scripts and analytics models, further extending the system’s capabilities.
• PowerBI: A powerful tool for creating interactive and insightful business intelligence reports, integrating seamlessly with the PI System.
• PI Interfaces: Enables reliable collection of data from multiple sources like OPC Servers, PLC, relational databases, Batch Execution Systems

Rationale for the Systems and Technologies Used

Each technology and system integrated by Réalta Technologies was carefully selected to meet the specific needs of the BioPharma site:

• High-Availability and Redundancy: The PI System architecture ensures continuous operation with minimal downtime, critical for maintaining uninterrupted production and compliance.
• Real-Time Data Visibility: Integrating PI Vision, Datalink, and PI Analytics provides stakeholders with real-time access to operational data, enabling proactive decision-making.
• Advanced Reporting and Analysis: Tools such as RtReports, PI EFGen, and PI Integrator for Business Analytics enable detailed reporting, exception-based review, and in-depth analysis of critical process parameters (CPP) and batch performance.
• Seamless Integration with Existing Systems: The PI System’s compatibility with DeltaV, Syncade MES, and various PLCs ensures a smooth integration process, preserving existing investments in technology.
• Customisable and Scalable Solutions: The use of Python and PowerBI allows for the development of custom analytics and reports, tailored to the site’s specific needs, while providing scalability for future expansion.

Use Cases and Benefits

The implementation of the High-Availability PI System has enabled the BioPharma site to achieve significant improvements in operational efficiency and data-driven decision-making. Key use cases include:

• Alarms Notifications and Reporting: Automated alerts and detailed reporting on alarms ensure quick response to critical issues, minimising downtime and enhancing safety.
• Downtime Reporting: Accurate tracking and analysis of downtime events help identify root causes and implement corrective actions, reducing production losses.
• Critical Process Parameter (CPP) Reporting: Continuous monitoring and reporting of CPPs ensure that production stays within defined parameters, maintaining product quality and compliance.
• Batch Reporting with Review by Exception Strategy: Streamlines batch reporting processes, focusing only on deviations and exceptions, which reduces the time required for quality reviews.
• Batch Analysis & Comparison Dashboards: Visual dashboards allow for easy comparison of batch performance over time, helping to identify trends and optimise processes.
• Energy Monitoring Dashboards: Provides insights into energy consumption patterns, enabling the site to implement energy-saving initiatives and reduce operational costs.

Conclusion

Réalta Technologies has once again demonstrated its expertise in implementing advanced technological solutions for the pharmaceutical industry. By deploying a High-Availability PI System at the BioPharma site, Réalta has enabled the site to achieve greater operational efficiency, enhanced data-driven decision-making, and improved compliance with industry regulations. The successful integration of multiple systems and the deployment of cutting-edge technologies highlight Réalta Technologies’ commitment to delivering customised, high-performance solutions that meet the unique needs of their clients.

If you’d like to discuss your challenges or how we can help your data work better for you, contact us today.

sales@realtatechnologies.com 

+353 21 2439113

FAQs

1. What is a High-Availability PI System?
   A High-Availability PI System is a robust data infrastructure that ensures continuous operation with minimal downtime. It is designed to collect, store, and analyse real-time and historical data, providing businesses with actionable insights and ensuring operational continuity.
2. How does the PI System enhance operational efficiency?
   The PI System enhances operational efficiency by providing real-time visibility into critical processes, automating alerts and notifications, and enabling advanced data analysis. This allows businesses to proactively address issues, optimise processes, and make informed decisions.
3. What is the role of PI Vision in the PI System?
   PI Vision is a visualisation tool within the PI System that allows users to create interactive dashboards and displays. It enables real-time monitoring of operational data, making it easier for stakeholders to identify trends, anomalies, and opportunities for improvement.
4. Why is integration with existing systems important?
   Integration with existing systems is crucial as it ensures that the PI System can seamlessly collect and analyse data from various sources without disrupting current operations. This preserves the value of existing technology investments and minimises implementation challenges.
5. How can businesses benefit from energy monitoring dashboards?
   Energy monitoring dashboards provide businesses with insights into their energy consumption patterns. By analysing this data, companies can identify areas of inefficiency, implement energy-saving initiatives, and reduce operational costs, contributing to sustainability goals.

In today’s data-driven world, businesses thrive on the ability to swiftly analyse and interpret vast amounts of information. Réalta Technologies, always at the forefront of technological advancements, has recently become a certified SEEQ Partner. With engineers now certified in SEEQ, and more undertaking the training via our SEEQ server access, Réalta Technologies is set to revolutionise data analytics for its clients. But first, let’s dive into what SEEQ is, its myriad benefits before discussing the value our SEEQ-certified engineers bring to Réalta Technologies and their clients.

So what is SEEQ?

SEEQ is a cutting-edge data analytics solution designed specifically for process manufacturing data. It facilitates the rapid investigation of data, providing users with insightful analytics that drive better decision-making.

SEEQ’s advanced capabilities in time-series data analysis, collaboration, and workflow automation make it an invaluable tool for industries such as pharmaceuticals, manufacturing, food & beverage and many many more.

What does SEEQ do?

Advanced Analytics:

SEEQ offers advanced analytics that help in understanding complex process data through statistical analysis, machine learning, and various modelling techniques.

Time-Series Data:
The platform is optimised for time-series data, making it ideal for industries that rely on continuous data collection and monitoring.

Integration Capabilities:

SEEQ integrates with various data sources, including historians, databases, and cloud platforms, ensuring smooth data flow and accessibility.

Collaboration Tools:

It includes robust collaboration tools that allow teams to work together efficiently, sharing insights and analytics in real time.

Scalability:
SEEQ’s scalable architecture ensures it can handle data from small operations to large-scale enterprises.

How will SEEQ benefit my Business?

SEEQ empowers businesses to gain deeper insights into their operations by transforming raw data into actionable intelligence. This leads to improved decision-making, optimising processes, and ultimately enhancing productivity and profitability.

Faster Time to Value:
With SEEQ, companies can quickly analyse vast amounts of data, significantly reducing the time required to derive meaningful insights. This speed translates to faster problem-solving and opportunity identification.

Cost Efficiency:
By streamlining data analysis processes and improving operational efficiency, SEEQ helps businesses reduce costs associated with downtime, waste, and inefficiencies.

Improved Collaboration:
The platform’s collaboration features enable teams to work together seamlessly, regardless of their physical location. This fosters a culture of shared knowledge and collective problem-solving.

What Value will Réalta Technologies SEEQ Certified Engineers add?

Réalta Technologies’ commitment to excellence is evident in its decision to have multiple engineers certified in SEEQ. But what does this certification mean for clients?

Deep Expertise:
SEEQ certified engineers possess a profound understanding of the platform’s capabilities and best practices. This expertise ensures that clients receive top-notch services tailored to their specific needs.

Customised Solutions:
Certified engineers can develop customised analytics solutions that align with the unique requirements of each client. This bespoke approach maximises the value clients derive from their data.

Efficiency and Accuracy:
With certification comes a high level of proficiency, enabling engineers to work more efficiently and accurately. Clients benefit from faster project completion times and more reliable outcomes.

Ongoing Support and Training:
Réalta Technologies’ SEEQ certified engineers provide continuous support and training, ensuring clients can fully leverage the platform’s capabilities long after initial implementation.

Réalta Technologies: A Trusted SEEQ Partner

By becoming a certified SEEQ Partner, Réalta Technologies has positioned itself as a leader in the field of data analytics. Our certified engineers are not just experts in SEEQ but are also dedicated to delivering the highest quality service to our clients. This partnership enhances Réalta Technologies’ ability to offer innovative solutions that drive success in an increasingly competitive market

Conclusion
Réalta Technologies’ new status as a certified SEEQ Partner, with a team of SEEQ certified engineers, marks a significant milestone in our mission to provide superior data analytics solutions. The enhanced capabilities of SEEQ, combined with the deep expertise of Réalta Technologies’ engineers, ensure that clients can unlock the full potential of their data, driving efficiency, productivity, and profitability.

For businesses looking to stay ahead in a data-driven world, partnering with Réalta Technologies means accessing the best in analytics technology and expertise. Ready to take your data analysis to the next level? Reach out to Réalta Technologies today and discover the transformative power of SEEQ.