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Category: Power BI

Custom Alerting With PowerApps

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

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

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

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

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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Introducing PowerApps

Jason Thomas has a great introduction to PowerApps:

you will be able to pass context aware data to a PowerApps app which updates in real time as you make changes to your report. Now, your users can derive business insights and take actions from right within their Power BI reports and dashboards. No need to switch tabs to open the separate apps, copy paste data from one window to another or worry about fat fingering the wrong customer id or invoice amount.

If you think about it, this is a game changer – you finally have a BI tool that allows you to collaborate and take actions right within the report. How many times have you looked at a report, found out an insight and wished that you could send an email to the account manager, only to forget later? Well, now you don’t have to worry about that, as I am going to show you an example of how we can collaborate by adding comments within the report (not just comments, but context aware comments, based on what you are selecting) as well as show how to send emails (to the appropriate people based on your selection).

This is an interesting concept and Jason has a detailed overview of it.

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Goal Tracking With Power BI

Stacia Varga uses New Year’s resolutions to motivate a Power BI tutorial:

As I was thinking about this relationship between goals and feedback, I thought Microsoft Power BI would be a great tracking tool. It’s free, so use it! In years past, I used spreadsheets or checklists in journals or OneNote, any of which is a fine way to accumulate a comprehensive list of all that a person wants to do. However, I never measured progress, thereby denying myself feedback. Consequently, I’d let myself get sidetracked during the year.

This year I promised myself I’d try a different approach and thought I’d share the process with you through a series of blog posts. Although I’m going to discuss goal-tracking from a personal point of view, you can also use the same techniques for your business-oriented goals. Either way, I hope you learn something about Power BI along the way and are inspired to do some goal-setting of your own.

It’s a good use of Power BI.

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Clustering The Power BI Gateway

Craig Porteous show how to cluster the Power BI Data Gateway to allow for disaster recovery:

I love PowerShell and I even wrote a module with functions to query Power BI metadata but there should always be another way to get this vital information.

The documentation I mentioned earlier points you to a PowerShell module file included in the November update. You can load this file & use the commands they provide to get information about your Gateway cluster and its members or make changes to clusters.

If it’s important enough to use, it’s important enough to include in a disaster recovery plan.

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Getting Dates Between Two Dates In Power BI

Imke Feldmann has created an M function to get the set of dates from a start date to an end date at some fixed interval in Power BI:

This function takes 3 parameters:

  1. From- or Start-date
  2. To- or End-date
  3. A selection of ONE of these intervals: Year, Quarter, Month, Week or Day

All dates will be created at the end of the chosen interval: So if you want to analyse events with a duration for example, where you want to transform your data to show one day per (monthly) event, this function generates month-end-dates for every month within the timespan. Please not that if the To-/End-date is within a month, the last element of the list will NOT be that day, but the day of the end of that month.

The default-value for the 3rd parameter is “Day”, so if you omit the specification, the function will return a list of all days in between.

Click through for the script and some explanation of the code.

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