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Category: Power BI

Power Pivot And Power BI Data Modeling

Avi Singh has a post on data modeling in Power Pivot and Power BI:

It was Greg, who suggested that we form a book reading club. Our first book was one I had heard about, but never read – The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling By Ralph Kimball. As a business analyst, I had leaned heavily on Excel, along with a mishmash of other technologies. Data warehouse and data modeling didn’t seem like topics that would be relevant to me; more for an IT/BI team perhaps. But I figured, it couldn’t hurt to learn something new.

Our book club meetings looked more as if, class was in session. We brought in our questions, and Greg patiently answered them, helping us realize the importance of the topics, and trade-offs involved in various choices. As things go, our reading club was disbanded before we were even halfway through the book. But the knowledge that I had gained, helped me grow by leaps and bounds in my Power Pivot and Power BI journey.

Kimball-style fact-dimensional modeling remains a brilliant solution.

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Getting Into Power BI

Jorge Segarra jumps into Power BI:

For my contribution to this contest I’ve decided to share with you a work in progress. If you know me, I’m a huge lover of Policy-Based Management. In fact, I’m actually part of the Enterprise Policy Management Framework (EPMF) project on Codeplex. T-SQL Tuesday event is normally a DBA-centric event so I figured I’d help the DBA crowd wrap their heads around how a BI solution can help them in their day to day.

What I did to kick start this effort was to create this Power BI report that allows you to explore the database repository that contains the EPMF policy evaluation results. The current EPMF project uses Reporting Services to deliver its reports. This won’t change. If anything I’ll be exploring new capabilities with SQL Server 2016 and R-integration. Here’s a screenshot of what the SSRS dashboard report looks like:

I like this post because most Power BI examples tend to be personal (Fitbit stats, etc.) or business-y.  This is a good example of a use of Power BI for back-office database administrators.

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Power BI With SSAS

Jens Vestergaard’s T-SQL Tuesday entry involves Power BI feeding from Analysis Services:

My story with this half-baked product (the Dashboard you are about to see), is that I needed some way of tracking performance on a couple of Analysis Services (SSAS) query servers. There are a lot of good posts and talks about how to collect and store performance counters and SSAS logs out there, and I suggest you look into this, this or that, if you need inspiration.

The current data set is about 200K rows, as I am sampling each server every 5th minute.

Both of these are valuable tools in a Microsoft BI environment.

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CSVs With Line Breaks In Power BI

Chris Webb talks about one of the banes of my existence:  flat files with “rogue” line breaks:

But what if you can’t fix the source data? I was asked this question the other week, and since I had been asked about it before and not come up with a good answer, I decided to spend some time researching the problem.

What I found was that it was relatively easy to write some M code that gave me the correct results, but very hard to write code that performed acceptably well on a large data set (I was testing on a CSV file containing almost half a million rows). Here’s the code for the function I ended up with:

It’s nice to see that Power Query & Power BI have methods to get around this sort of issue, but it sounds like even those methods are limited in value.

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Power BI Plus Fitbit

Rob Farley visualizes his Fitbit data with Power BI:

I added a column: RollinAvgSteps = AVERAGEX(FILTER(fitbit_export_20160214, EARLIER(fitbit_export_20160214[Date])>=fitbit_export_20160214[Date]),fitbit_export_20160214[Steps])

…which takes the average of my steps to date. There are a bunch of ways to achieve this, but this is the way that I chose. And you can see that the average line is (happily) improving! Oh, and because I pulled down the extract on the 14th, there’s a dip at the end. My numbers were much healthier by the end of the day, and despite spending way too long NOT walking, I did about 7244 steps that day.

You can see the result at http://bit.ly/RobFitbit

I like the rolling average that Rob added in.

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Embedded Power BI Dashboard

Rob Collie has a great example of what Power BI can do with his embedded, “real-time” (realish-time, at the very least) analytics dashboard:

Yeah, that’s a DAX-powered, Power BI dashboard, right here in our website – a website that runs on WordPress, which is Linux for crying out loud.  Don’t know what Linux is?  No worries, just translate it as “there’s zero Microsoft software behind PowerPivotPro.com, and yet – BAM!  Power BI, right here!”

And the dashboard in question is a near-real-time view of the traffic on this very site!  Check back in an hour and you will be able to “see” yourself on the map (especially easy if you use one of the “rarer” browsers.)

Check out the technical walkthrough if you’re interested in doing something similar yourself.

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Visualizing Power BI DMV Queries

Chris Webb shows us how to use Power BI Desktop to visualize DMV queries:

However, running DMV queries against a Power BI Desktop model (which of course runs a local version of the same engine that powers Analysis Services Tabular and Power Pivot) and more importantly doing something useful with the information they return, isn’t straightforward. You can run DMV queries from DAX Studio but that will only give you the table of data returned; you need to copy and paste that data out to another tool to be able to analyse this data. Instead it’s possible to use Power BI Desktop’s own functionality for connecting to Analysis Services to connect to its own local data model and run DMV queries.

It looks like there are some limitations to this technique, but for quick and dirty work, it works.

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HDInsight + Power BI + Spark

Reza Rad has a nice walkthrough on integrating several powerful technologies:

Power BI can connect to many data sources as you know, and Spark on Azure HDInsight is one of them. In area of working with Big Data applications you would probably hear names such as Hadoop, HDInsight, Spark, Storm, Data Lake and many other names. Spark and Hadoop are both frameworks to work with big data, they have some differences though. In this post I’ll show you how you can use Power BI (either Power BI Desktop or Power BI website) to connect to a sample of Spark that we built on an Azure HDInsight service. by completing this section you will be able to create simple spark on Azure HDInsight, and run few Python scripts from Jupyter on it to load a sample table into Spark, and finally use Power BI to connect to Spark server, load, and visualize the data.

If you’re totally unfamiliar with Spark but interested in data processing, now’s a good time to start digging into the topic.

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