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Category: Power BI

Stream Analytics And Power BI

Brad Llewellyn gives us a demo on connecting a Stream Analytics stream to Power BI for data analysis:

We understand that streaming data isn’t typically considered “Data Science” by itself.  However, it’s are often associated and setting up this background now opens up some cool applications in later posts.  For this post, we’ll cover how to sink streaming data to Power BI using Stream Analytics.

The previous posts in this series used Power BI Desktop for all of the showcases.  This post will be slightly different in that we will leverage the Power BI Service instead.  The Power BI Service is a collaborative web interface that has most of the same reporting capabilities as Power BI Desktop, but lacks the ability to model data at the time of writing.  However, we have heard whispers that data modeling capabilities may be coming to the service at some point.  The Power BI Service is also the standard method for sharing datasets, reports and dashboards across organizations.  For more information on the Power BI Service, read this.

Brad has a nice demo, so check it out.

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Daylight Savings Time Calculations In Power BI

Fred Kaffenberger shows us how to convert UTC to local time zones with daylight savings time:

Quick tip for DST Refresh Date function Power BI Service. I’ll put the code up front, and explain it below. I’ll also say a bit about how to use it at the end. The United States and other places, like Australia, have a pesky thing called Daylight Savings Time. This means that in Central Time US, the offset from Universal Time Coordinated (UTC) is sometimes -6 and other times it’s -5. While Power Query can convert time zones, it doesn’t handle DST. And, my users like to see when the reports were refreshed as a step in evaluating data quality. In 2019, US DST is from March 10 – November 3 (2 AM local time). So, the functions here need to be updated every year.

As promised, here’s the custom function. 

Click through for the custom function and a nice explanation of how it works.

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Copy Measures Between Power BI Files

Matt Allington shows us how you can copy measures between PBIX files:

Warning!
Ok, here is the warning.  This is not supported by Microsoft.  If you do this and it breaks your model, you will not get support from Microsoft (or me for that matter).  So, back everything up and keep the backups – don’t delete them.  Consider yourself suitably warned 🙂 .

This warning just makes me more likely to do it…

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Multi-File Power BI

Marc Lelijveld shows us how to break up a single Power BI desktop file into several:

Normally a Power BI Desktop file (PBIX) contains your queries, data model, and reports (visualization). Looking at a multi-file strategy, we split this up into two (or more) files.

The first file only contains the queries and data model. The second file is directly connected to the first one (direct query) and reads the data model. The file it selves includes all report content like visualizations, booksmarks and everything related to that. By working this way, you will be able to build multiple reports based on the same dataset.

Click through for a demonstration.

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Power BI Dataflow Use Cases

Reza Rad gives us the value proposition behind Power BI Dataflow:

If you don’t have an account in Azure or you don’t have a subscription that you can use for Azure Data Lake, No need to worry! You can still use Dataflow. The whole process of storing data into Azure Data Lake is internally managed through Dataflow. You won’t even need to login to the Azure portal or anywhere else. From your point of view, in the Power BI website, you create a dataflow, and that dataflow manages the whole storage configuration. You won’t need to have any other accounts or pay anything extra or more than what you are paying for Power BI subscription.

Click through for use cases and some tips.

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Using Plotly In Power BI

Kara Annanie shows how you can R integration in Power BI to push Plotly visuals to users:

In the example, above, we’ve created a line chart visualization using Plotly and we’ve decided to put labels on the graph, but only on the first and last points of the line graph. This graph would be particularly useful to show 13 months of data overtime, where the left-most label shows January of last year, for example, and the right-most label shows January of this year, for example. The user could still view the trend across the year between both January data points.

Click through for a pair of videos and some notes on how to get started.

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Power BI “Is Nullable” Property

Chris Webb notices a new column property in Power BI Desktop:

I was, naturally, curious about what it did and I couldn’t find any documentation so I did a bit of investigation of my own and asked a few people at Microsoft.
It turns out that it is primarily intended for validation purposes, so that if you know a column should never contain a null value and then, at a later date, a null value does appear in that column then you’ll get the following error when you try to refresh a table in Import mode:

Column ‘MyColumn’ in Table ‘TestTable’ contains blank values and this is not allowed for columns on the one side of a many-to-one relationship or for columns that are used as the primary key of a table

Read on for more information. It looks like it works just as you’d expect.

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Common DAX Error Messages

Marco Russo takes us through some of the more common Power BI error messages around writing DAX:

The message should help the author fix the code, but sometimes the text suggests a possible action without describing the underlying issue. The goal of this article is to explain the more common DAX error messages by providing a more detailed explanation and by including links to additional material. If some terms are not clear, look at the linked articles or consider some free self-paced training such as Introducing DAX.

Click through for several examples.

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Bubbling Up HTTP Status Errors In Power Query

Tony McGovern takes us through a method involving Power Query + M of giving end users useful information when a web request fails:

So how does this relate to error tables? Like most well-documented APIs, the U.S. Census Bureau API has a page devoted to listing and describing all the possible response codes that can be returned by their service. I take this information and build an internal table within the query that defines and describes these response codes in my own words. I’m now able to throw custom messages that make the difference between a 400 response code and a 404 response code more obvious.

For example, in the code below, I use the Error.Record function to create individual records that allow me to catch these unsuccessful requests and throw my own custom error messages to the user. I then create an extra field in each record called ‘Status’, which maps each HTTP response code returned by the API to a corresponding error message of my choosing:

There’s a bit of work, but the end result is a fairly simple explanation for end users.

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