Category: Power BI

Chris Webb has bad news for people with tables holding 2 billion-plus rows in Tabular format:

What’s more, the error will always occur even if you apply a filter to the table that returns less than two billion rows. The same problem occurs with some other functions, such as Percentile(), but it’s worth pointing out that the vast majority of DAX functions work as normal with tables with more than two billion rows – for example, in the pbix file used here the Sum() and CountRows() functions not only work fine but return instantly.

I haven’t seen that many Power BI examples with 2 billion or more rows in a table, but it can be an impediment when trying to use Analysis Services Tabular in cases with enormous amounts of data.

Matthew Roche shows off the “column from examples” feature in Power Query:

Here’s the quick overview:

1. In the Power Query editor in Power BI Desktop, choose “Column from Examples” from the “Add Column” tab.
2. Enter the values that the new column should have for rows that are already in your data set.
3. Review the values that Power Query is suggesting for the other rows, and when they are all correct, choose OK, and then say “Ooooooohhhhh” when Power Query does all the work for you.

It’s a little hard to see from Matthew’s image but this is a great feature when you have a regular pattern but don’t want to put together a regular expression yourself.

Treb Gatte takes us through Publish to Web and the importance of getting the correct licensing for Power BI:

Some folks, either to avoid the need to buy a Microsoft Power BI license or in trying to embed Microsoft Power BI content in an On-Premises site like Microsoft SharePoint 2013, published their content using this function.

The risk is that if the content is on a page that gets indexed by a major search engine, like Google, the embed code will likely live in Google’s index forever. Then anyone can search for your data.

Read on to see the right way to do this. Treb also notes that there are good use cases for Publish to Web; you just have to make sure yours is one of them.

Matt Allington takes us through a new feature in Power BI:

Now back to the point of this post.  As of June 2019, it is possible to pre-filter slicers as well.  It may seem weird, but this previously wasn’t possible – it seemed weird to me, anyway.  This is now fixed and it is possible to use the side filter pane in the same way as other visuals.  I can think of quite a few useful scenarios, including:
– Hiding the dreaded (Blank) in a slicer.  [Actually, please don’t do that, but instead fix your data model].
– Filtering out items not relevant (eg category managers may only want to see their own products)
– Hiding items with no sales

Read on for a few examples of how to use this.

Teo Lachev shows us how you can unpivot multiple columns in Excel using Power Query:

The user wants to unpivot the data by rotating the three header rows (Scenario Type, Month, and Year) from columns to rows. The issue is that the headers span three rows. If you just select these columns and unpivot, you’ll end up with a mess. And Power Query operates on row at the time so you can’t reference previous rows, such as to concatenate Scenario, Month, and Year. We can do the concatenation in Excel so we have one row with column headers, such as Actuals-Jan-2018, Actuals-Feb-2018, and so on, which we can easily unpivot in Power Query. But if we can’t or don’t want to modify the Excel file, such as to avoid the same steps every time a new file comes in?

Click through for a sample file which shows how you can do this.

David Eldersveld builds out a Power BI accordion filter:

The Power BI custom accordion relies on Bookmarks and Buttons as key elements. I’ve only created two categories in my accordion. I’ll be honest–it’s probably more work than it’s worth to keep track of different buttons due to positions as well as what’s visible or hidden for each bookmark. The thought of expanding to three categories is a bit daunting. Why is that?

Read on to see why (hint: combinatorial explosion).

Rob Collie explains how to calculate Value Above Replacement:

Let’s say you’re trying to improve the fuel efficiency of your car, and you have a budget of $100 to make those improvements.  Furthermore, let’s say that you can only spend your budget on three different kinds of improvements:  better tires, better spark plugs, and a better exhaust system.

The simple answer, of course, is to buy the Best of each part – the best Tires, the best Sparkplugs, and the best Exhaust System.

But what if Reality rears its head and rudely insists that the Best Costs More?  What if there are a range of options available in each bucket, with varying price AND effectiveness?  Then what?

Read on for the solution which has not nearly enough baseball.