Power BI as a data visualization tool

Presenting the data

The final step in a data modelling and reporting process is to present the data to the users. Year after year, data visualization plays a more important role as a growing number of advanced technologies are available for this purpose, and business users would like to use increasingly personalized and interactive reports and dashboards.

It is also an important factor that the user should be able to make changes to the analyses themself. In addition to choosing the right data warehouse, the choice of data visualization tool has now become a cardinal question as well.
Microsoft is the market leader in BI Platforms and Analytics, Power BI is one of the most widely used data visualization tool (based on Gartner’s 2020 Magic Quadrant survey).

Power BI has been available to the general public since July 24, 2015. We describe in this review how it’s suitable for both data modelling and data visualization, while in a following article we’ll detail the tool’s potential in machine learning and Artificial Intelligence.

Power BI as a product

Power BI’s great advantage is being a Microsoft product its well-known interface, so users don’t have to learn a whole new environment, because Power BI’s integration with Ms Office is outstanding.

Power BI’s pricing is highly flexible, now available from 10USD per account. Of course, a free trial period is available, so it can be tested without any commitment.

It makes it easy to share information, either across the company or within our team. Power BI reports can also be shared outside the organization, assuming that the given user has a Power BI account. With the help of the common platform (Power Platform) the report or dashboard can be published and it will be immediately available to colleagues, and they can also work together on the same report. The queries created can be viewed in the Power BI mobile app. A special feature is that the Power BI Mobile iOS app is already integrated with Siri shortcuts, so Siri can be used to open reports, just saying “Siri, open the sales report!”.

Power BI is leading in the utilization of possibilities lying in artificial intelligence for BI. Functions such as ‘Quick Insights’ helping discovering trends in data or ‘Q&A’ answering user’s questions are good example.

Power BI is constantly “evolving”, new developments and features are regularly released, helping to get the most out of our data.

The components of the Power BI data visualization tool

• Power BI Desktop: used to create reports.
• Power BI service: cloud-based service to publish the prepared reports, and the reports created by colleagues can be viewed here.
• Power BI mobile application: to access the tool on smartphones.
• Power BI reporting server: allowing the use of reports behind the firewall, developed for companies not yet willing to store their data in the cloud. It’s simple to switch to the cloud-based Power BI service later.

Power BI has a variety of unique visual and data analysis solutions, including among others:

• Location-based data visualization
• Interactive filtering
• Ability to create custom visual themes
• Row-level security
• Drill-down within a dashboard
• Creating personal template system
• Slicer

Power BI data extraction methods

When creating a report /dashboard in Power BI, the first step is to select the data extraction methodology. Data can be extracted from a variety of source systems, such as SAP, HANA, Oracle, MS SQL, SharePoint, Excel, csv, etc. Power BI can extract data from the source system(s) in two ways:

• direct query method
• import method

Using the direct query method, the data extraction from the source system occurs while the report / dashboard runs, therefore each run queries the source. Using an appropriate source system, a quasi-real-time reporting can be achieved, which is advantageous. But the drawback is that besides creating a heavy burden on the source system, the runtime of the source data extraction is added to the Power BI report / dashboard display time.

Using the import mode, it is not necessary to follow the classic “reporting overnight charges the following day” methodology, because the extraction to update the report a few times a day or even hourly can be scheduled. Another advantage of this method is that the previous result will be deleted at the end of the upgrade process, so the Power BI report / dashboard can be displayed with sufficient performance even during the upgrade.

The Power BI data visualization tool and the SAP BW/HANA

The previous SAP BW versions’ integrated and free front-end tool – among others – was the Business Explorer, which had a solid Excel integration. With the introduction of BW4HANA, SAP discontinued the free front-end tool, making the use of third-party solutions more relevant.

With previous non-HANA based data warehouse versions – although with significant limitations – it’s also possible to take advantage of Power BI capabilities. Data can also be extracted from 7.3 non-HANA based SAP-BW systems, using query as a data source. In this case, data from data content validated by business users over years can be transferred, which requires significantly less testing effort, and a data-cube can be the basis for the Power BI reporting.

However, with a HANA source the range of options is much more extensive, all advantages of virtual data modelling provided by HANA can be utilized, therefore it is recommended to do a significant part of data modelling in HANA. However, Power BI is not only an exploiter-viewer tool, but also capable of data modelling. Since HANA and Power BI are two separate systems it can be used beneficially, what is a source for Power BI is a freely transformed and aggregated data arriving from HANA. Using this method, the amount of data needed to transfer to Power BI data visualization tool can be reduced, and at the same time the division along main characteristics allows the data from multiple, even non-SAP sources to be connected and displayed in a single report in Power BI.

During Power BI data-modelling new tables (e.g. DAX, with functions and union) can be created and between these relationships can be defined from the tables imported into the model.

Power BI and SharePoint

Various easily and user-friendly maintainable SharePoint lists, which can be used without leaving the familiar Microsoft environment have significant user base.

Even for a production company using SAP, it is very difficult to create a “single and true” product master that can be fully used for analysis, because a significant number of attributes are maintained in SAP, but others are handled in “The Excel table” or “On Share” by separate users.

Previously, somehow all data had to be forced into the data warehouse or the base system for example, but Power BI can easily use Excel tables or SharePoint lists as a source.

Using this integration function helps to solve several previously relevant issues:

• no need for the business user to learn a new environment or tool,
• no need to “develop into” the affected fields into the base system or data warehouse,
• on the front-end data can be viewed and analysed in a single report.

Power BI and a Power BI connected to an SAP HANA system offer a large number of reporting, data visualization, and data analytics opportunity. Once the systems are available, only a suitable partner is needed to get the most out of our data!

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