Reporting Historical Data Using Microsoft Power BI

Power BI is a powerful tool for data reporting. It functions not only as a tool for preparing dashboards or simple paginated reports, like its predecessor SSRS (SQL Server Reporting Services), but also provides tools for advanced transformations and calculations. Its integration into smart RDM is another step toward unifying standards for data access within a single application. This integration is achieved through the Power BI embedded cloud service.

How does smart RDM enhance the use of Power BI?

Smart RDM improves data reporting by combining the capabilities of the AVEVA PI System with the advanced features of Power BI. The preferred data source for integrated reporting in Smart RDM is the PI system, due to the direct data manipulation capabilities provided by:

• A form module that allows precise editing of attribute values.
• An events module for managing attribute values and event timeframes.

However, reporting is not limited to data from the PI system. Users have full flexibility in choosing their data sources. To accommodate this, we have prepared a Big Data module that, through the support of custom scripts, allows interaction with virtually any data source.

What are the benefits of reporting historical data in Power BI?

Here are some of the key benefits of using Power BI for reporting historical data:

• Trend Analysis: Identifying long-term patterns and trends in data helps forecast future outcomes.
• Data-Driven Decision-Making: Access to historical information enables more informed and accurate business decisions.
• Interactive Visualizations: Power BI offers the ability to create interactive visualizations, allowing deeper exploration of historical data.
• Comparative Analysis: Comparing data across different periods facilitates progress assessment and comparative analysis.
• Online Accessibility: Reports can be shared online, providing constant access to historical data for all authorized users.
• Visual Appeal: Power BI allows for the creation of visually attractive presentations of historical data, making them easier to understand and interpret.
• Data Integration: The platform allows for the integration of historical data from various sources, offering a more comprehensive view of business situations.

Three Steps to Effective Data Visualization

Power BI enables efficient analysis of historical data by transforming raw data into useful information through three main modules:

• Power Query: This is a tool for data extraction, transformation, and loading (ETL). This module should be familiar to any analyst that had previous experience with a bit more complex excel projects, as exactly the same power query.
• DAX (Data Analysis Expressions): A formula language used for creating advanced calculations and analyses. Though popularized by Power BI, DAX is also used in other applications like MS SQL Analysis Services and Dynamics 365. It allows the creation of custom measures and calculated columns that respond dynamically to contextual changes on dashboards, offering over 200 functions for complex calculations, including time analysis and data aggregation.
• Relationships Module: This module facilitates the creation of links between different datasets, essential for designing data models that enhance the performance and scalability of projects and support query optimization.

Data Prepared – What Next?

Effective visualization in Power BI involves selecting the appropriate chart types to best represent data and convey key information. When creating a report in Power BI, users can choose from a variety of native visualizations such as bar charts, trend charts, decomposition trees, maps, or even AI-supported visualizations. It is crucial to maintain simplicity, interactivity, and visual consistency. Advanced techniques, like combined charts or custom visualizations, should be used to maximize visualization legibility.

Typical Applications – Most Common Reports

Power BI is utilized across various reporting needs, including but not limited to:

• KPI Reports: These include metrics like OEE, Energy Efficiency, Failure Rate, Quality, Performance, Unit Production Cost, Waste, Plan Fulfillment, Laboratories, etc.
• Environmental Reports: Such as CO₂, NO_x, Water, etc.
• ESG Reports: Covering Environmental, Social, and Governance criteria.

Data quality is the foundation of well-created, automated reports.

Added Value of the Embedded Version

The embedded version of Power BI, enabled through smart RDM, brings several advantages, including:

• Embedding in Applications: Fully leveraging Power BI capabilities within Smart RDM applications.
• Cloud Environment: Utilizing a cloud-based infrastructure for enhanced scalability and accessibility.
• Integrators for Data Export: Ready-made integrators for exporting data from OT systems to the cloud.
• Production Data Warehouses: Creation of dedicated data warehouses for production data.
• Automated Report Generation: Automatic generation of shift, daily, and monthly reports.
• Data Verification and Approval: Ensuring data accuracy and approval processes.
• Mobile Access: Viewing reports on mobile devices for greater flexibility.

In summary, Power BI, embedded through smart RDM, can be an efficient and flexible tool to support production performance evaluation. Our specialists are available to assist from the initial design and cloud environment installation to report creation and ongoing service.