Devin Knight continues his Power BI custom visuals series:
In this module you will learn how to use the Dot Plot Custom Visual by MAQ Software. The Dot Plot is used to show distribution using dots among multiple categories or attributes.
Dot plots are nice because they tend to be informative while keeping the ink to whitespace ratio low.
Reza Rad shows how to build merge joins between date ranges in Power Query:
Customer’s table has the history details of changes through the time. For example, the customer ID 2, has a track of change. John was living in Sydney for a period of time, then moved to Melbourne after that.
The problem we are trying to solve is to join these two tables based on their customer ID, and find out the City related to that for that specific period of time. We have to check the Date field from Sales Table to fit into FromDate and ToDate of the Customer table.
This is a common type 2 SCD scenario. I’d be concerned that this solution would not work with large data sets which may already be pushing the size limits of the Vertipaq engine.
Matt Allington covers some of the basics of DAX:
Do I need to learn the DAX language?
You certainly do not need to know how to write DAX to get started with Power BI. Power BI is the newest business intelligence tool that leverages the DAX language (via Power Pivot) and it is definitely possible to get started and build some reports without learning any DAX at all. If you are a “consumer of reports” that other people produce for you then you certainly don’t need to learn any DAX. However if you are someone that wants to do your own adhoc (or structured) analysis of data using Power BI, Power Pivot for Excel, then you will definitely want to learn to write some DAX in order to get value from what these new tools have to offer.
It’s a good intro if you aren’t familiar with DAX.
Paul Turley has a video showing how to use row-level security with Power BI:
The best method to implement row-level security in a published Power BI model or SSAS Tabular model consumed from the Power BI service will depend on will depend on your data and requirements. The method I demonstrate here is one of the most flexible approaches and one that I commonly use in my projects.
Click through to watch the video.
Dusty Ryan shows off What-If Analysis in Power BI:
Next, I’m going to create a calculated measure that multiples Revenue Last Year by Revenue Target % Value. Here’s the formula for the calculated measure:
Revenue Target = [Revenue Last Year] * [Revenue Target % Value]
Now I’m going to add this new measure, Revenue Target, to my line chart. And now when I use my slicer slider bar, I can dynamically change my Revenue Target line on the chart!
This is pretty cool. Definitely check out Dusty’s example; it’s something that might make many an executive happy.
Meagan Longoria shifts our perspective by 90 degrees:
Back in January 2016, I wrote a blog post explaining a DAX workaround that allows you to put measures on rows in a matrix in a Power BI report. I’m happy to say that you no longer need my workaround because you can now natively put measures on rows in a matrix in both Power BI Desktop and PowerBI.com.
This is accomplished via a new formatting option for the matrix.
Click through to see how to pull this off.
When we need to process streams of real-time data, Storm is a great contender. Examples of streaming data are the number of consumer clicks and navigations on a website, IIS or user logs, IoT data, and social network information. In all these scenarios, we use real-time data processing. Apache Storm can process real-time unbounded streams of data.
The term “unbounded” defines streams of data with no start or end. Here, the processing of data is continuous and in real-time. Twitter is a good example. Twitter data is continuous, has no start or end time, and is provided in real-time by millions of Twitter users around the world.
Storm wouldn’t rank in my top three technologies for doing this, but it certainly does the job.
Devin Knight continues his Power BI custom visuals series:
In this module you will learn how to use the Quadrant Chart Custom Visual. The Quadrant Chart is used to show a distribution of data across separate quadrants.
There’s an interesting mix of 2D layout plus bubble size. This is probably one of the better custom visuals available.
Mitchell Pearson shows how to slice results based on text input:
In this installment of the Problem, Design, Solution series we are going to show you how to perform a text search using slicers in Power BI, this simulates a “LIKE” type search. In the following screenshot you can see that when “Tax” is selected all records in the table that have “Tax” anywhere in the record are returned, likewise whenever “IT” is selected from the slicer all records in the table that have IT in them are returned. Hope you enjoy this post!
Click through for the explanation, followed by a video that walks you through the process.
Ginger Grant shows how to build a dynamic date dimension in Power BI using either DAX or M:
Recently I needed to create a date dimension for a Power BI model as there was not one in the source database. There are two different ways that I could do this, using DAX from the Modeling Tab within the Data View or using M via the Query Editor window. As a general rule, when it is possible data manipulation should be done in M as it offers a greater level of compression. In this case though I am using a function in DAX, which is not the same as creating a calculated column.
Read on to see code examples for each method, as well as Ginger’s analysis.
Kevin Feasel
2017-08-21
Power BI, Visualization
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