Pivot your table-relationships in Power BI and Power Pivot

While the relationships view of the datamodel provides a very good overview which tables are connected to each other, one cannot see at a glance on which field they are connected to each other.

This is where a pivot table-view of the field-connections can be really helpful:

Pivot-table-view:

Table-Fields-Connections in Pivot-View

 

Here you see the tables on the many-side in the rows and in the columns are the tables on the one-side (of course you can change that). Add some slicers if your model is very large.

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Performance Tip: Partition your tables at crossjoins where possible – PowerQuery PowerBI

Recently I’ve distributed some techniques for partial matches or relative joins between tables using PowerQuery or the query editor in PowerBI. They are very flexible and powerful – yet slow.

To improve performance you can check if there is a chance to “partition” your table using a Table.Group. If you have an equality expression in your statement like we had in our rolling-12-months-exercise here for example:

You can boost performance into a different dimension by grouping your table on the “Associate”-table instead like this:

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Use Slicers for Query Parameters in PowerBI

Reading Rob Collie’s latest cool blogpost on how to retrieve slicer selections in Power BI, I couldn’t stop thinking of how awesome it would be, if we could use this technique to pass slicer selections as query parameters to the M-queries in the query editor. Not only would we have a very convenient user interface, but – what’s actually more important at the moment – we could pass multiple values as parameters to our queries, as this is not possible at all currently:

But how to fetch them? Rob’s post simply uses cross-filtering to show the values in a separate visual. In Excel we have cubefunctions where we can pass the slicer(-selection) as a parameter. Igor Cotruta, who is describing beautiful PBI-hacks on his blog here, kindly helped me out on this: “Via DMVs. Check $system.discover_sessions for the field sessions_last_command”. This worked perfectly into the following function, in which you just have to pass the name of the measure as a parameter:

Make sure that you have used that measure on one of your visuals, as otherwise the function cannot harvest it. Also you have to first save the file and then push the refresh-button in order to trigger the correct refresh. The above function sort of “reads the current PBI file from outside”, so it will only see the saved version.

When you do the first refresh, a dialogue will pop up, where you just have to accept the default values like this:

The example in the file below fetches temperature data where every selected year will create a unique URL and the results of all those calls is consolidated into one table. But of course, this technique can also be used to pass multiple parameter values to SQL-commands or others.

A final note: The query to extract the slicer parameters from the DAX-statement is not particularly robust and you might have to adjust it, if your slicer-selection-strings contain special characters.

Download for logged-in subscribers SlicerParameter2.zip

Edit 25-Sep-2017: Adjusted the code to retrieve PortID.

Also: You have to disable privacy-settings for this code to run. And: This is a solution that will only work in Power BI Desktop and not in the service.

Recap:

  1. If you create a new measure or adjust this file to your settings, you have to use the new measure in report somewhere and save the file. This is necessary to “initialize” the measure to your model so that it can be seen in the query editor.
  2. From then on, when you use it: Just change the selection in your slicer and click “Refresh”

Enjoy & stay queryious 🙂

Blending data in PowerBI like in Tableau

Today I came across a question in the PowerBI-forum if blending data was possible in Power BI like in Tableau. Although I wouldn’t necessarily recommend it, it’s definitely is a nice challenge. So the following function will interlace the rows from 2 tables like the blending-function in Tableau does. Just that we cannot use any aggregators on the attributes and are not able to use measures, as this takes place in the query-editor.

In our example we have a table with actual figures and one with budget figures:

We want to add 2 columns from the budget table to the actual table: “Amt” and “Qty” (red). Where there’s no match of budget – figures with actuals, there need to be added rows which hold only values from the budget figures (yellow):

Blended data like in Tableau

So we could do a join in full-outer-mode, but then we would need to find a way to put the date- and AccountNo-values into the existing columns of the actual figures. Instead we will identify those rows who need to go below the actuals and then do a join in left-outer mode just to add the values of the 2 new columns.

You need to feed this function the following parameters:

  1. Name of the primary table (“Actuals”)
  2. Name of the secondary table (“Budget”)
  3. Key column names of the primary table (“Date”, “Account”)
  4. Key column names of the secondary table (“Date”, “AccountNo”)
  5. Column names for the value columns (“Amt”, “Qty”)

Table.BlendRows

 

File with sample: BlendDataTableau.zip