Like many other services and tools in the market, when a product passes certain popularity, normally we see some rumors and myths and misconceptions about it spreading around. Power BI also has that kind of myth and misconceptions. In this article, I’ll uncover five of the most common myth and misconceptions about Power BI.
Misconception 1: Power BI is not an enterprise reporting tool, it is only good for self-service.
This is a misconception. And it is there because many people who have heard of Power BI, are not aware of the data modeling engine, the data transformation, and other main components of it. Maybe they just know Power BI as a visualization tool.
Power BI came to the market with the promise of binging data analysis to everyone using extra-ordinary self-service ability using Power BI Desktop and Power BI Service. However, Power BI itself is built on top of Microsoft enterprise data analysis toolset.
The modeling engine of Power BI uses Analysis Services tabular in-memory engine, which is powerful, fast, and reliable. This is the same engine used in Azure Analysis Services. Analysis Services technology in Microsoft has a long history, it started in 2000, and it is a technology with a great maturity level over this 20+ years.
The Data transformation engine of Power BI uses Power Query, which is a powerful data transformation engine. This came into Excel in 2013, but before that, the M expression language was available internally in Microsoft for applying data transformation. The Power Query evolved a lot during many years, and it became a reliable and powerful technology. Nowadays we use Power Query not only in Power BI but also in dataflow, which gives you the ability to implement ETL online separately from the data model.
The visualization engine of Power BI is a powerful component that enables you to do both dashboard-style analysis and also paginated reports (for printing).
Power BI leverages a hosting service called Power BI service, which works with Microsoft OneDrive and Teams and other services to enable the organizational level sharing, deployment, and administration of the reporting objects.
Explaining the entire Power BI ecosystem needs a post (or even a book) of its own. What I want to emphasize here is that Power BI came a long way and is sitting on the shoulder of giant and powerful technologies in the area of enterprise reporting. Power BI is definitely a service you can rely on in an enterprise reporting scenario.
Misconception 2: Power BI is not suitable for big data sets, it is slow when we have a large volume of data.
This is another big misconception about Power BI. From my point of view, this misconception comes from not being familiar enough with how to build reports with Power BI with large data sets. I often come across reports that are slow because the modeling is not done in the right way, or some other performance considerations have been missed.
Power BI certainly can handle big data. And when I say big data I mean billions, trillions, and even more data rows. Of course, building a report to deal with such a dataset requires special care and attention. But Power BI can handle it. I have previously explained how trillions of rows can be easily and very fast sliced and diced in Power BI.
This uses a number of techniques and technologies in Power BI. Things such as combining DirectQuery and Composite Mode together in a Power BI model, the usage of aggregations, and some other performance tuning considerations can make your report super-fast even if there are hundreds of trillions of rows of data.
Misconception 3: Power BI is not rich in visualization (Compared to other tools in the market)
This is another misconception. Power BI itself has many powerful visualization features, charts, and configurations. It also enables you to use a visual that someone else has built (with the visual SDK provided by Microsoft). There are over 200 custom visuals that you can use in a Power BI report.
There are powerful visuals such as Charticulator, which is not just another visual. It is a visual that you can build other visuals with it. Charticulator by itself is a world of data visualization capabilities.
Let aside that Power BI enables you to use other languages such as R and Python which enables you to use their visualization elements too.
Misconception 4: Power BI is only useful if you are using other Microsoft products and Services.
Power BI is a Microsoft service and product. However, Power BI can get data from over 80 different data sources. You can connect to an Oracle database, to a text file, to an API, and many other data sources. You do not need to have other Microsoft services installed to use it. So whatever data source you have, there is a high chance that Power BI can get data from it directly. Even if it can’t, there are options such as ODBC connectors or APIs, or other methods that enable Power BI to get data from that source usually.
I have customers who are not even using Office365 for the email system, Teams, or any other Microsoft products. However, they do their data analysis using Power BI, and it helps them a lot.
Misconception 5: Everyone can learn Power BI in a day
Power BI has many components. Mastering Power BI takes a lot of time. There are aspects that you can pick up on very fast, such as building visualizations. And there are aspects that you have to continuously learn throughout time, such as modeling and DAX.
You may choose to self-learn using many of the blogs, videos, and other resources. Or you may want to do formal training for that. Either way, becoming a Power BI expert requires time and has a learning curve. It is not something you can do in a day or week or maybe even a month. You have to keep learning and practicing it.
There are, of course, many other misconceptions about Power BI. I am sure many of you heard about them too, please write it down in the comments below, I like to hear them from you.