Category: Power BI

Rob Collie uses DAX to find disproportionate sentiment on a per-group basis:

My wife loves to travel AND she loves data, so it’s no surprise that she showed me the infographic in question.

“Oh come on, California residents don’t visit the Philippines more often than any other country.”  That was my first reaction.  (Mexico is the overwhelming #1 destination, basically for every state… because Cancun.  And because there are so many Mexican-Americans).

“Ah…  but California residents DO visit the Philippines disproportionately more often than they ‘should,’ according to national averages!”  That was my dawning second realization (and confirmed by the fine print of the Orbitz article, even though the article’s title suggests otherwise.)

So, how do we do that in DAX?  Pretty simply, actually.

I’m mentally working out whether this could be useful in anomaly detection.

Cedric Charlier continues his series on fixing up an Excel file.  First up is turning results into an enumeration:

We’ve previously decided that a DON’T KNOW, shouldn’t influence our average of the answers. To apply this decision, we just need to filter the table Result and remove all the values equal to 0 (Enum value of DON’T KNOW). Then we calculate the average and subtract 1 to get a value between 0 and 4. Coooool, except that if we’ve no value non equal to 0, it will return -1 … not what we’re expecting. We’ll need to validate that the average is not null before subtracting 1.

The next post involves converting respondent information into a dimension:

In this table, only the results with a QuestionId equal to 111 really interest me for a merge with the existing table Respondent. If you’re familiar with the UI of Power BI Desktop then you’ll probably think to create a new table referencing this one then filter on QuestionId equals 111and finally merge. It’ll work but applying this strategy could result in many “temporary” tables. A lot of these small tables used only for a few steps before merging with other tables tend to be a nightmare for maintenance. You can use the “Advanced formula editor” to not display this kind of temporary tables and embed them in your main table.

Read on for more.

Nicolo Grando shows how to create anti-slicers in Power BI:

A normal slicer can be tedious when you want to show everything apart from just one or two entries in your filtered tiles – don’t take your finger off the Ctrl key! You could always turn on Select All, then unselect the items. But you may not want Select All enabled, and it’s not available for chiclets. Or you could use Visual/Page/Report level filters, but these are not available in dashboards or publish-to-web. So you may be interested in an anti-slicer? There are many ways to do this, this is one approach.

This is an interesting problem to solve, and I think this is a nice solution.

Ginger Grant shows that data sets don’t need to be exactly the same for Power BI to combine their contents:

Recently I worked on a Power BI project where I needed to merge data provided in spreadsheets. The spreadsheets came from different vendors and while they contained mostly the same data, the columns were not in the same order. I wanted all of the data to reside in one table. In Query, that means that I wanted to Append the data. The files which I were merging were very wide, and I missed the fact until after I was done that some of the columns were in different order. Power BI is smart enough to figure out the order on its own. I didn’t need to change the order of the columns at all, as long as they have the same column names. Here’s an example using three different files.

That’s a sign of a smart tool.

Cedric Charlier has started a series on dealing with hierarchical data in a not-so-hierarchical format:

To load this Excel file in Power BI, I’ll just use standard functions and define a first table “Source” that won’t be enabled to load in report.

My next task will be to create a table (or dimension) with the different questions. I also want to include a hierarchy in this dimension: I should be able to browse the questions by categories and sub-categories.

Let’s create a new table named “Question” by referencing the “Source” table. Then remove the other columns than A and B.

The curse of Excel is that it’s so easy to build a data set in strange ways that make it hard to integrate later.