Monday, August 21, 2017

Power BI #2: Getting To Know The Power BI Desktop

The Power BI Desktop is the main tool you would be using in creating Power BI reports. You can freely download it here from Microsoft




Once you are done installing it. You get a startup screen like the one below.


There are two major parts of Power BI Desktop you will need to get very familiar with:

1. The Designer part.



2. The Query Editor part.


Let's start first with the Designer part. It is the window you are presented with upon launching Power BI. It has four main sections.


  1. The menu section comprising File (for Open, Save, Options/Preference settings etc.), Home, View and Modelling.
  2. The Report, Data and Relationship section
  3. Page section (like Sheets in Excel), and
  4. The context based section that shows Fields and Visualization when you are in Reports, Fields only when you are in Data and nothing when you are in Relationship.
Now to the Query Editor. It is the exact equivalent of PowerQuery (now merged into Get & Transform Data in Excel 2016). Its main function is to help you wrangle data before they are fully loaded/downloaded into the Power BI. So instead of downloading a 16 GB database table and then specifying which fields/rows to keep and which to discard, you can do the specifying using just a preview of the data and only import just the very data you want/need. This is a life and time saver. And space/memory saver too. Then you can do some very interesting and complex stuff you can't do from the Designer part -- like merge or append data from different sources, unpivot and a few other things I find myself doing repeatedly on client/commercial projects.

You get to the Query Editor from the Home menu in the Designer part.


And it has four sections too.

  1. The menu section
  2. The Queries section
  3. The Data section, and
  4. The Query Settings section (which only shows up when you have/selected a Query)
And that is it for this second tutorial post in the new beginner to expert series I am doing on Power BI. Cheers!