Leveraging Microsoft Power BI for Enterprise Self-Service BI

Power BI is a data analytics service by Microsoft to aid the process of self-service BI. The tool has been GA since July 2015 and has progressed a lot with its monthly updates. The innovation can also be seen in the leader position of Microsoft in 2018 Gartner Magic Quadrant report for Analytics and BI platforms.

But what else is unique about this tool? How does it perform in a larger BI landscape? How well does it integrate with other tech stacks like SAP? The complete findings, compiled in a deck with 45 slides, were presented online – a recording of which is available here. In this blog, we’ll review our approach and summarize the findings.

The Power BI suite provides a wide range of offerings from simple solutions to complex applications:

We also explore the following self-service BI capabilities of the tool:

1. Acquire data from a wide range of sources (SQL, SAP, Big Data, Azure, Cloud, etc)

Microsoft and Azure based data sources offering more functionality both at the desktop and service level as it belongs to the same tech stack.

2. Perform robust data preparation to further enhance the data

3. Build visualizations using simple drag and drop

4. Compose reports and extend to dashboards

5. Collaborate with other using Power BI Service and access via O365

The webinar also covers other interesting features like:

Custom visualizations and themes
DAX Scripting for advanced data preparation
R based Query Editing and visualizations
Question & Answers with Insights and Cortana Integration
Preview options to enable new features
ArcGIS Maps, What-if parameter analysis, Slicer based filtering
RLS (Row Level Security)
Pricing and Licensing
SAP and Microsoft Integration

Conclusion

When considering self-service, Power BI alone might do a good job connecting with multiple data sources and enhancing it locally or collaborating with small teams.

Ref : https://docs.microsoft.com/en-us/power-bi/whitepapers

But when extending this to an enterprise level application, we would need to leverage the Microsoft technology stack like Azure Platform and Azure Analysis Service to provide live data with RLS enabled.