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Category: Power BI

Excel Data Analysis with Python

Chris Webb takes us through a new add-in for Excel:

In the Power BI/Fabric community everyone is excited about the recent release of Semantic Link: the ability to analyse Power BI data easily using Python in Fabric notebooks. Sandeep Pawar has an excellent blog post here explaining what this is and why it’s so cool. Meanwhile in the Excel community, everyone is excited about the new integration of Python into Excel. But can you analyse Power BI data in Excel using Python? Yes you can – so as my teenage daughter would say, it’s time for a crossover episode.

Click through for an example of it in action.

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Updates to Power BI Field Finder

Stephanie Bruno has an update for us:

The Power BI Field Finder is a standalone .pbix file you can download and hook up to your reports and data model to. The Field Finder helps you visually analyze where fields are used in reports.

I’ve used this to great effect on a prior project where I had to figure out what was going on in a report with about 20-25 pages that other people had put together.

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Refreshing a Direct Lake Power BI Dataset in Microsoft Fabric

Chris Webb refreshes our memories:

If you’ve heard about the new Direct Lake mode for Power BI datasets in Fabric you’ll know that it gives you the query performance of Import mode (well, almost) without the need to actually import any data. Direct Lake datasets can be refreshed though – in fact, they refresh automatically by default – and if you look at the dataset’s Refresh History you’ll see there’s a Direct Lake section which sometimes shows errors:

Chris goes on to ask and answer the question, what does it mean to refresh a Direct Lake dataset if you’re not actually importing the data into Power BI?

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Conditional Formatting in Power BI with Field Parameters and Calculation Groups

Marco Russo and Alberto Ferrari perform some formatting:

If you want to build a report where the user can choose what measure to show, you have two features available in Power BI: field parameters and calculation groups. There are pros and cons to either technique – however, we are not about to talk about those. We narrow our scenario down to a specific requirement: we want to change the color of the value depending on the measure selected.

For example, suppose we let users choose between Sales AmountMargin, or Total Cost. In that case, we might provide visual feedback about the measure selected through different colors: black for Sales Amount, green for Margin, and red for Total Cost.

Click through for that example, though I will say that the color choices are hard to differentiate if you have protanopia and even more difficult if you have deuteranopia, so about 2% of the male population would struggle with interpreting this measure. People with protanomaly and deuteranomaly (about 6% of men) wouldn’t have too much difficulty with this particular color pairing.

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Power BI Themes and Gallery

Seth Bauer has an announcement:

The Power BI Tips Theme Generator tool already allows you to easily interact with, and adjust, all the visual properties, wireframes, etc… How could we possibly make Power BI Theme building an effortless experience? We start with building it all for you, then letting you adjust it!
The all new Gallery feature represents a significant leap forward in simplifying the theming process for all. This feature is especially for the business users! But, it also opens up exciting opportunities for the Power BI community to contribute in the future as well.

Read on to see how this works.

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Always Use Explicit Measures in Power BI

Ed Hansberry has some advice for us:

All of your analytics in Power BI are done with measures, and there are two ways to create measures. It is important to understand the difference between the two methods. If you drag a field from the data pane directly into a visual, that is an implicit measure. The model usually wraps it with SUM(), but other aggregations are possible, like COUNT() or AVERAGE().

Read on to see what’s wrong with using implicit measures, as well as how to make these explicit.

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Distinct Counts in Power BI and KQL

Dany Hoter needs a distinct count:

Calculating distinct counts on massive distributed datasets is not trivial.

Kusto (aka Azure Data Explorer/KQL database in Fabric) dcount and dcountif functions use a special algorithm to return an estimate of distinct counts

The new functions count_distinct and count_distinctif were recently added to calculate exact distinct counts. These two functions are much more expensive than the original ones.

Read on for more details on how this all works.

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Automated Power BI Visual Testing with PBI Inspector

Chris Webb phones a friend:

This week, one of my colleagues at Microsoft, Nat Van Gulck, showed me a cool new open-source tool he’s been working on to make VisOps for Power BI much easier: PBI Inspector. What is VisOps? I’ll admit I didn’t really know either, so being lazy I asked Nat to write a few paragraphs describing the project and why it will be useful:

Read on for Nat’s description and an example of PBI Inspector in action.

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