Data Warehouses: What Do I Know? Well, I'm no expert. I learned Power Pivot and Power BI through Excel. What I know is from helping to build a SQL data warehouse. That is, I've worked with a data warehouse pro.…
From the Water Cooler As a 'water cooler' of sorts for this community, we meet some amazing people. Matt Mowrey shares with us a really useful technique to create a discoverable income statement using PowerPivot. This post runs a little…
As I have started working with clients around training/consulting, I am surprised by how often I find tables that have been flattened, i.e. the data tables have been combined (joined) with lookup tables, to produce a really wide table with everything and the kitchen sink in it. Maybe that’s to be expected; after all that is the modus operandi when working in Excel. That’s the first habit that I try to break. I would nominate this for the top 5 mistakes but that already has 6 on the list 🙂
Usually it is just a matter of changing how data is being pulled from the source to address this issue, and go from flat table to separate Data and Lookup tables (Star Schema). However at times, your data source itself may only have the flattened version of data. If you have little control/influence over the data source, you may be stuck with a flat table. Or not!
Flat to Star: Using DAX Query
The first thing that should come in your mind to deal with this should be Power Query, and we will cover that. But this time let’s try to use DAX as a query language for this purpose. Our sample data, is a flattened file which has sales data as well as product attributes. We would like to separate these into distinct power pivot tables.
The hardest part is getting started; for that watch the video. I will skip to the DAX query used, with a tip of the hat to Marco and Alberto from whom I have learned so much (and continue to do so).