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2016: A Powerful Year for Power BI

2016 was an eventful year for a lot of reasons. Most importantly (okay, okay—maybe not most importantly), Microsoft solidified its position as a top choice among vendors for BI analytics tools. Boasting ease of use coupled with the ability to create powerful data visualizations, Microsoft pulled ahead of competitors.

Don’t believe me? Check out Microsoft’s position on the Gartner Magic Quadrant for BI and Analytics Platforms. The left is from February 2015, and the right is February 2016.

However, it doesn’t stop there. This momentum continued through the rest of 2016 and into 2017. Below is the most recent Gartner Magic Quadrant for BI and Analytics Platforms from February of this year.

But how did Microsoft pull so far ahead?

Easy—Microsoft listened to its users and its critics.

Microsoft is constantly working to improve its offerings, specifically Power BI. Microsoft created an online forum for Power BI where users can suggest and vote for product enhancements. The enhancements with the most votes get implemented (assuming the enhancement is feasible). It really is that simple.

When I have introduced Power BI to clients in the past, many were excited by the product, but voiced concerns about limitations in functionality and security. This spurred me to get on the Power BI Idea forum. I found that many other users shared these concerns. Microsoft addressed these and many others by introducing a multitude of updates and enhancements over the past year. While there are too many to call out here, below are a few of my favorites (some of which I personally voted for—the system works!):

  1. A Date Slicer
    Power BI uses slicers to allow end users to filter data in a report. In October of 2016, Microsoft introduced a Date Slicer, making it easier to filter a report based on dates. There were plenty of workarounds to get the normal slicers to behave properly with dates, but the new date slicer makes the experience easier and more visually pleasing. It makes use of a slider bar and a calendar interface to allow users to select a specific date or date range.
  2. The Analytics Pane with Forecasting
    In September of 2016, Microsoft introduced the Analytics Pane, allowing users to easily create and format dynamic reference lines on certain visual types. In November of 2016, Forecasting was officially added to the Analytics Pane. Forecasting is a special feature which allows developers to predict and display future data values based on the current available information and trends. Below is an example of forecasting in action. The highlighted gray area of the chart displays the forecasted values.
  3. Row Level Security
    I have had several clients ask for a way to restrict data within a report or dashboard based on the user accessing it. While there are always workarounds, Microsoft added Row Level Security to Power BI data models which can be used to restrict data access for given users, making this task easier than ever.
  4. Conditional Formatting in Matrices and Tables
    Of all the enhancements, this is the one I was most excited about. It’s one that end users have asked me for time and time again: the ability to format matrices and tables based on data values within each cell. With the addition of conditional formatting of matrices and tables to Power BI in May of 2016, this is possible. Developers can call out important values by making them a different color, which makes it easier for end users to gain insight from a table at a glance.

The above updates represent only a small portion of the long list of enhancements made to Power BI since its creation. The biggest takeaway from this post is that Microsoft is constantly updating and improving Power BI based on what users and developers want to see.

To see more updates, or get more detail on the updates listed in this post, check out

To request an enhancement, or to vote for your favorites, visit the Power BI Idea forum.

When using the idea forum, it’s always a good idea to do a quick search first, to see if your idea or a similar one has already been submitted. If it has—vote for it!



About The Author

Data Solutions Consultant

Lindsay is a Data Solutions Consultant at the Columbus branch of Cardinal Solutions. She has experience in all aspects of the Business Intelligence life cycle, from data modeling and ETL to report and dashboard creation.