Introduction

SAP systems are pivotal in business analytics, offering robust data management and integration capabilities. By harnessing tools like SAP HANA and SAP BW, organizations can perform advanced analytics, generate real-time insights, and support data-driven decision-making. These systems streamline operations, enhance reporting accuracy, and provide a comprehensive view of enterprise performance, driving strategic growth and efficiency.

Integrating SAP systems with Power BI provides a powerful combination for data analysis and visualization, enabling organizations to leverage their SAP data effectively for better decision-making. Here's a detailed guide on how to connect SAP systems with Power BI and the benefits of doing so.

Power BI Supports below SAP Connectors:

1. SAP HANA Database
2. SAP BW Warehouse Message Server
3. SAP BW Warehouse Application Server

Prerequisite

Power BI needs an ODBC driver to be installed to leverage these connectors to get SAP systems data.

SAP HANA Database:

You should install SAP HANA ODBC Driver on your local system to connect to SAP HANA Data using Power BI.You can get the same from https://support.sap.com/en/my-support/software-downloads.html 

SAP BW Warehouse:

To utilize the SAP BW Message/Application Server connector within Power BI Desktop  the installation of SAP .NET Connector version 3.0 or 3.1 is necessary.. The SAP .NET Connector is available for download directly from https://support.sap.com/en/product/connectors/msnet.html .

During the installation process, ensure that you choose the option “Install assemblies to GAC” within the Optional setup steps.

Connections types

Both the SAP Connectors support Import and Direct query connections from Power BI. You can refer our article here to understand the concepts of Import and direct query in Power BI.

When you are connecting Power BI to SAP HANA Database, there are two options available:

1. Treat SAP HANA as Multi Dimensional Source

In this scenario, Power BI acts similarly when it  connects to other multi-dimensional sources such as SAP Business Warehouse or Analysis Services. When connecting to SAP HANA with this configuration, a single analytic or calculation view is chosen, granting access to all its measures, hierarchies, and attributes in the field list. 

When visuals are generated, aggregate data is consistently fetched directly from SAP HANA. This method represents the preferred approach and serves as the default setting for new DirectQuery reports on SAP HANA.

2. Treat SAP HANA as Relational Source

With this approach, Power BI treats SAP HANA as a relational source, providing greater flexibility. However, you need to be cautious to ensure that measures aggregate correctly and to avoid performance issues. 

To use this option, go to File > Options and settings > Options > DirectQuery and check the box for “Treat SAP HANA as a relational source.

When deciding whether to treat SAP HANA as a multi-dimensional or relational source in Power BI, it’s crucial to align with your business requirements. Let’s explore the benefits and constraints of each approach:

Multi-dimensional source (default):

 Advantages:

• Simple setup: Power BI automatically selects a single analytic or calculation view, making it easy to get started.
• DirectQuery: Visuals retrieve aggregate data directly from SAP HANA.

 Limitations:

• Limited flexibility: You can only work with the measures, hierarchies, and attributes from the selected view.
• Potential performance bottlenecks: Aggregations may not always behave as expected

.

Relational source:

 Advantages:

• Greater flexibility: You can connect to multiple tables/views and define relationships.
• Custom queries: You have more control over the data retrieval process.

 Limitations:

• Careful aggregation: Ensure that measures aggregate correctly.
• Performance considerations: Be cautious to avoid performance issues

Case Study:SAP Report on Strategy 

We've generated a report using SAP data and utilized SAP connectors for Power BI. This report was designed for strategy teams to grasp different KPIs and metrics, aiding their comprehension of business operations and addressing critical inquiries regarding the company's sales performance. Let's walk through it together to explore the KPIs and uncover insights from the data.

1. This page offers a comprehensive overview of turnover, growth, backlog, and sales in both the current year and year-over-year (YOY) timeframe. It provides a consolidated view that enables business users to assess the company's performance in the current year at a glance.These insights/KPI’s include

• Turnover: Describes the company's turnover for the current and previous year.
• Backlog: Details the current backlog of the company.
• Growth: Illustrates the year-over-year (YOY) growth of the company across various categories.

       Additionally, other KPIs are provided to give business users a comprehensive view of performance.

2. The Turnover page provides insights into KPIs related to the company's overall turnover, incorporating various dimensions. Business users gain a multidimensional perspective of turnover across different groups within the company.These insights/KPI’s include

• Trend Analysis: Illustrates the turnover value trends over the past few years, highlighting the percentage increase or decrease.
• Top/Bottom Growing Products: Displays the top 8 and bottom 8 product groups showing year-over-year (YOY) growth. This aids in identifying top performers and areas needing attention for underperforming products.
• Supplier Performance: Offers insights into how different suppliers have performed in terms of turnover and growth in the current and previous years for the company.
• Turnover Value by Material and Product: Provides a comprehensive table view to understand the turnover value over the last 4 years categorized by material and product.

Also, there are filters provided for users to refine and analyze the data. These filters enable users to focus on specific values or dimensions using the available slicers. Additionally, users can choose the metric type as Quantity or Value (EUR).

3. Another page dedicated to Turnover Analysis expands on additional KPIs to offer valuable insights to users. These insights and KPIs are:

• Turnover by Country: Displays turnover across different countries on a map.
• Turnover by Sales Group: Provides details on turnover by various sales groups in the current and previous years.
• YOY Growth by Sales Group: Highlights year-over-year growth of turnovers within different sales groups.

 Additionally, slicers are provided for Year, Month, Sales Groups, and Product Family, enabling users to filter and analyze data based on specific dimensions of interest.

4. This page offers the capability to view various metrics across different dimensions in a single consolidated view. Users can select metrics using the Metrics slicers, which then display corresponding data in the visuals. For example, currently displaying Backlog, OOH, and DNI metrics. The page includes the following KPIs:

• Monthly Trend: Illustrates the monthly trend for the current year.
• By Country: Displays metrics by country using a map visualization.
• Sales Groups: Details metrics across different sales groups.
• Table View of Backlog, OOH, Turnover, and Backlog: Provides a comprehensive view of all metrics over recent years and allows data export to Excel.
• Supplier and Product Hierarchy: Explains metrics categorized by suppliers and product hierarchy.

5. The Overview page offers various perspectives to present Total IAM in comparison to product hierarchy and region. Here, users gain insights into how metrics compare within specific regions or product hierarchies against overall company performance. This helps identify the performance of particular regions in a given year.

• Table View of Product Family: Provides insights into the performance of each product family using metrics such as previous year, year-to-date (YTD), delta, backlog, and OOH, alongside total IAM and selected regions from the slicer.
• Table View of Region: Details the performance of each region with metrics including previous year, YTD, delta, backlog, and OOH, alongside total IAM and selected product family from the slicer.
• YTD Turnover by Product Family/Region: Charts the year-to-date turnover across different regions and product groups.

Additionally, we have other charts that analyze turnover, growth, and trends across dimensions such as RSM and product hierarchy.

Conclusion

Overall we can conclude that, Integrating SAP data into Power BI enhances analytic capabilities, enabling real-time insights and informed decision-making. This synergy facilitates agile reporting and visualization, empowering organizations to optimize operations and drive growth. 

By leveraging the SAP connector, businesses can foster a data-driven culture that translates analytics into actionable outcomes, ensuring competitive advantage in the market.