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Category: Power BI

Controlling Power BI Visual Visibility

Published 2019-04-25 by Kevin Feasel

Matt Allington shows how we can take one Power BI visual and use it to control the visibility status of another visual:

I have written a few articles in the past that toy with the ideas of changing visibility and text colour based on selection.  I started to wonder if it was possible to make a visual appear (or not) based on a selection from the user.  There is no out of the box way to do that today. It is possible to use bookmarks to show an hide an object, but the user must click a specific button to do this. I want the user to be able to interact with a report and see (or not see) a chart based on some valid selection across the report.  Microsoft is already working on building expression based formatting across the breadth of Power BI however as of now the only item you can change is the header in a chart.

Hopefully this gets better over time.

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Running Spark MLlib to Feed Power BI

Published 2019-04-24 by Kevin Feasel

Brad Llewellyn shows how you can take Spark MLlib results and feed them into Power BI:

MLlib is one of the primary extensions of Spark, along with Spark SQL, Spark Streaming and GraphX.  It is a machine learning framework built from the ground up to be massively scalable and operate within Spark.  This makes it an excellent choice for machine learning applications that need to crunch extremely large amounts of data.  You can read more about Spark MLlib here.

In order to leverage Spark MLlib, we obviously need a way to execute Spark code.  In our minds, there’s no better tool for this than Azure Databricks.  In the previous post, we covered the creation of an Azure Databricks environment.  We’re going to reuse that environment for this post as well.  We’ll also use the same dataset that we’ve been using, which contains information about individual customers.  This dataset was originally designed to predict Income based on a number of factors.  However, we left the income out of this dataset a few posts back for reasons that were important then.  So, we’re actually going to use this dataset to predict “Hours Per Week” instead.

Check it out. And Brad’s not joking when he says the resulting model is terrible. But that’s okay, because it was never about the model.

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Power Query Container Size and Performance

Published 2019-04-24 by Kevin Feasel

Chris Web looks into what changing the Power BI Dataflow container size does for us:

Currently there is no way to change this 256MB in Power BI Desktop or Excel although someone has already posted a suggestion on the Ideas site to allow us to change it. How much of an impact does this actually have on refresh performance though? Without the ability to change this setting it’s hard to say, but I suspect it could be significant and that a lot of Power Query performance problems could be explained by this behaviour.

The situation is different in the Power BI service, where I understand there is a limit on the overall amount of memory that a single Power Query query evaluation can use.

Read on to understand the differences here between running on Power BI Desktop and running in the Power BI service, as well as a bit of testing on Chris’s part.

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Aggregating Only Visible Values in DAX

Published 2019-04-24 by Kevin Feasel

Alberto Ferrari shows how you can calculate a sum based only on the visible values and ignoring the missing cases:

These measures produce the correct figures month by month. However, at the year level the number of working days might be too big whenever there are incomplete months – this always happens before the end of the year, or when the first month with sales is not January as in the following example. As you can see in the following figure, in this case the yearly value of SalesPerWorkingDays is lower than the value of any month, which does not make much sense.

Click through for the solution.

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Power BI Report Builder Map Gallery Customization

Published 2019-04-22 by Kevin Feasel

David Eldersveld shows off how you can customize maps in the Power BI Report Builder Map Gallery:

One of the defining features of Power BI’s [paginated] Report Builder vs the current geospatial offerings in Power BI Desktop is the native support for ESRI Shapefiles. If you have worked with maps in Report Builder over the years, you may have used the Map Gallery. The Map Gallery offers a collection of built-in geographies, but you can also customize and enhance what’s available out of the box.

David takes us through an example of simplifying one map, but the same technique can help in other ways.

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Emailing Data From Power BI Via PowerApps and Flow

Published 2019-04-18 by Kevin Feasel

Erik Svensen investigates how to email specific records of data from Power BI:

One of my clients called me the other day and asked whether it was possible to export the selected order that was selected in the current report page – as she wanted to send the information to another user. I explained the export data feature from the visual action menu but she didn’t want to download a file and then locate that and then switch to Outlook and click new mail – type the correct the e-mail and attach the file – that was not very Power like – to much clicky clicky – because all the data was actually available when she had filtered the report for that particular record – the e-mail she wanted to mail the data to and off course the data she saw on the screen.

Hmm… Let’s see how we can use the PowerPlatform stack to solve this requirement.

Erik got everything working, so check it out.

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Scaling Power BI Premium Capacity

Published 2019-04-17 by Kevin Feasel

Matt Allington gives us instructions on how to scale Power BI Premium capacity:

This is the third article in my series about how to make Power BI Premium more affordable for small to medium sized enterprises (SMEs).  In my first article I explained the problem and the logic behind how to configure a workable solution. In my second article I provided step by step instructions on how to configure Flow to start/stop Power BI Premium capacities.  In the article today I am covering a way to scale the capacity up/down either on demand, or on a timed schedule.

The cloud is generally more expensive than on-prem, though it can potentially become cheaper if you are smart about scaling and have more scaling-friendly workloads. Matt even provides a really cool cost analysis to help you figure out what (if anything) you end up saving using this technique.

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Power BI Helper April 2019 Edition

Published 2019-04-15 by Kevin Feasel

Reza Rad announces an update to Power BI Helper:

Previously you could use Power BI Helper to connect to a model in Power BI Desktop and analyze that model, getting the list of all tables, columns, measures, alongside with measure dependency and modeling advise, and also documenting everything at the end. The good news is that now with having XMLA endpointavailable, you can connect directly to Power BI datasets in the service, and get all those functionalities with that.

Read on for the full change set.

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