Since the incremental refresh is already available with a Pro license, it was time for me to deal with this topic.
In the Power BI community, I found out that the known documentation describes how to set up an incremental refresh, but the examples are always based on a single query. In practice, however, combined queries from several subqueries are quite common.
Analyzing your customers is crucial for your business especially if you have a lot of customers.There are many ways and tools you could use to do this type of analysis, but Power BI is probably the most efficient analytical tool.
In this post, I put together some of my most comprehensive tutorials around customer analysis using Power BI. This will serve as your guide on how to complete quality customer analysis in your own business environment. You’ll see how I analyze customer trends and behavior over time using DAX formulas and the power of creating great visualizations.
Time Intelligence is a neat feature in Power BI, and, if we understand a few necessary aspects of how it works, then designing a robust data model becomes a straightforward task. For a beginner, it becomes elementary that we all understand what it takes to build a robust data model with Time Intelligence. A few frequently used Time-based calculations are Year-over-Year variation, comparing performance from the previous month or previous year the same month, YTD, QTD, and MTD. Time Intelligence functions make this task relatively simple.
The coronavirus pandemic is currently spreading around the globe. Two guys, Ben Sassoon and Sam Harris, have created a website https://howmuchtoiletpaper.com/ which explains that you do not need to hoard toilet paper. The website calculates the amount you need to survive a quarantine without changing your habits. Cool stuff. But what does it have in common with Power BI? Let’s find out.