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Category: Power BI

Switching Power BI From Imported To Live Query

Published 2018-01-31 by Kevin Feasel

Dustin Ryan shows us a neat hack to turn a Power BI Desktop file which uses an imported data model into one which uses Live Query:

In this blog post, I’m going to walk you through modifying a Power BI Desktop file with an imported data model to use an external data model hosted in Azure Analysis Services or SQL Server Analysis Services 2017. This isn’t supported by any stretch of the imagination but if you’re in a pinch and have to convert a Power BI Desktop file from an imported data model to Live Query then this may be helpful to you. Also, this method works as of the January 2018 release of Power BI Desktop but there’s no guarantee that this method will work in future releases of Power BI Desktop.

I was inspired to write this blog post after reading this post in the Power BI community forums by odegarun. It’s a great post with some good instructions, but I wanted to provide a clearer walk through as well as validate a couple other things with the process for my customers and anyone else that might be interested.

Check it out with the understanding that this is not a supported operation.

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The Benefits And Risks Of Sharing In Power BI

Published 2018-01-30 by Kevin Feasel

Steve Hughes explains the implications of sharing a Power BI report:

The primary reason to use share is to distribute content outside the context of a Power BI App. Power BI Apps should be your first mechanism for sharing content within your organization. It requires more thought and planning which is typically a good idea with your companies data. However, there are times when sharing makes sense. With the ability to share reports, you can limit sharing to specific areas. Also, you may want to create a “one-off” report for use in decision making but not something to be deployed in the long term.

Sharing is very different from deploying Apps. App deployment is not that difficult to do, but prevents sharing and is much easier to manage access.

Read on for Steve’s thoughts, including his hesitancy toward sharing en masse.

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Data Migration And Visualization With Data Factory And Data Lake

Published 2018-01-30 by Kevin Feasel

Matt Basile has a video which shows him taking raw data in S3, moving it to Azure Data Lake Storage using Azure Data Factory, and then visualizing it with Power BI:

While this seems like a lot of parts just to copy a few files, it’s important to note I only scratched the surface of what ADF can do.  Think of ADF as an airline company that manages and enables cargo (data) movement between cities (data sources).  A pipeline represents the overall goal of moving certain cargo from one city to another. The linked service is the airport, which provides a landing point and access control for the cities. The dataset is the list of cargo to move, the activity is the flight itself, while the integration runtime is the airport infrastructure that makes the cargo movement possible.  A single pipeline requires all these objects to run successfully; however, many pipelines can use these same objects to complete different tasks.  Once you’ve created these data factory objects, it is straightforward to layer on additional functionality or more pipelines. ADF also has visual tools that make building these objects a breeze – to build my pipeline, all I had to do was click on “Copy data” in the visual tools start menu and follow the steps provided.

Matt has a video demonstrating the process as well.

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Visualizing Progress Using Power BI

Published 2018-01-26 by Kevin Feasel

Stacia Varga methods of visualizing progress toward a goal using Power BI:

Another interesting way to look at goal tracking for a goal in which time is an important element, such as my daily Move goal, is to use a KPI visualization.

Just as many businesses use KPIs, which is an abbreviation for key performance indicators, I can use a KPI to see my current metric value, as of the last date for which I have collected data. In Power BI, not only can I see this value, but I can also see how it compares to the target at a glance, through the use of color. Red is bad and green is good, by default, but I can use the formatting options to change this. And I can see how the value trends over time, much like my current line and clustered column chart does.

Click through for several techniques.

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Custom Alerting With PowerApps

Published 2018-01-22 by Kevin Feasel

Jason Thomas shows how to create custom PowerApps alerts:

So this happened yesterday – one of my customers pinged me and asked whether it is possible to set customized data alerts for her end users? I froze for a second, knowing that such a functionality is not available out of the box but knowing how flexible Power BI is, I decided to explore her use case further. Worst case, I know I have the backing of the world’s best product team, and could submit a request to build this for us. Basically, she wanted her end users to get data alerts if specific products got sold in the last 24 hours (which should have been easy with the regular data alerts functionality in Power BI), but the challenge was that she wanted her users to set (add/delete) their own products. As I said earlier, this functionality is not available out of the box but with the PowerApps custom visual for Power BI and some DAX, we can definitely create a workaround.

Read on to see how it’s done.

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Building A Comparer For The Power BI Table.Group Function

Published 2018-01-22 by Kevin Feasel

Imke Feldmann shows off what you can do with the fifth parameter in Table.Group:

The Table.Group-function will pass 2 parameters to the function in the 5th arguments if it is used: For GroupKind.Local this is group-columns-record from the initial/first row of the table/group and the respective record of the current row.

As long as the comparer-function returns 0, the current row will be regarded as belonging to the group: This is a match in the Comparer.OrdinalIgnoreCase-function and also the value of false (which makes the syntax a bit counterintuitive here in my eyes)

Interesting reading.

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Visuals I Like

Published 2018-01-18 by Kevin Feasel

I continue my series on dashboard visualization:

This leads me to a little bit of advice for choosing bars versus columns.  You will want to choose a bar chart if the following are true:

  1. Category names are long, where by “long” I mean more than 2-3 characters.
  2. You have a lot of categories.
  3. You have relatively few periods—ideally, you’ll only have one period with a bar chart.

By contrast, you would choose a column chart if:

  1. Viewing across periods is important.  For example, I want to see the number of critic reviews fluctuate across the season for each of the TV shows.
  2. You have many periods with relatively few categories.  The more periods and the fewer categories, the more likely you are to want a column chart.
  3. Category names are short, by which I mean approximately 1-3 characters.

Some people will rotate text 90 degrees to try to turn a bar chart into a column chart.  I don’t like that because then people need to rotate the page or crane their necks.  In that case, just use the bar chart.

I like Cleveland dot plots, but they’re not implemented at all in Power BI and the two add-ons in the store aren’t that great either.  Also, there’s bonus material explaining why The Punisher season 1 was better than Daredevil season 1.

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Measuring Progress With Power BI

Published 2018-01-16 by Kevin Feasel

Stacia Varga shows how to use Power BI to simplify data analysis, using the example of New Year’s resolution goals:

First, the actual data represents the accumulation of data by day from the beginning of the year, whereas the target data represents the final tally at the end of a defined period. Each goal has a different frequency: daily, quarterly, and weekly. Currently, the comparison between actual and target data makes it appear that I’m falling way short of my goals. However, even if I were making solid progress on my goals on a daily basis, the comparison of the two values will never meet until the end of the defined period for any given goal. I need a way to prorate the target data so that I can more reasonably measure my progress.

Second, displaying the actual and target values in a table requires me to do mental math to determine how close (or not) I am to achieving my goals. Now, I’m pretty good at mental math, but a better way to see progress is to use data visualizations. I’m sure you’ve heard the saying… A picture is worth a thousand words.

This is a great post if you’re interested in getting started with Power BI.

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Analyzing Data Professional Salary Data

Published 2018-01-15 by Kevin Feasel

Ginger Grant has built a dashboard to analyze data professional salaries:

In the survey for 2018, the people who made the most money were from Hong Kong with an average salary of $263,289.  Before you start planning on moving, you will might want to look at the data a little closer.  There were 2 people who responded from Hong Kong.  One of them said he was making over 1.4 million dollars, the highest amount reported in the survey.  Given the fact that we only have two responses from Hong Kong, we will be unable to draw a definitive conclusion with 2 records. To be able to answer that question, more analysis will need to be done on the location and salary information and you will probably want to add market basket criteria because a dollar say in Hong Kong doesn’t go as far as the average apartment rental is $3,237 a month as it does say in Uganda where the rent is around $187 a month.

Click through to see the final product and grab a copy of her dashboard.

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