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Category: Power BI

Data Classification In Power BI

Published 2017-04-14 by Kevin Feasel

Steve Hughes describes how Power BI data classification works:

Power BI Privacy Levels “specify an isolation level that defines the degree that one data source will be isolated from other data sources”. After working through some testing scenarios and trying to discover the real impact to data security, I was unable to effectively show how this might have any bearing on data security in Power BI. During one test was I shown a warning about using data from a website with data I had marked Organizational and Private. In all cases, I was able to merge the data in the query and in the relationships with no warning or filtering. All of the documentation makes the same statement and most bloggers are restating what is found in the Power BI documentation as were not helpful. My takeaway after reviewing this for a significant amount of time is to not consider these settings when evaluating data security in Power BI. I welcome comments or additional references which actually demonstrate how this isolation actually works in practice. In most cases, we are using organizational data within our Power BI solutions and will not be impacted by this setting and my find improved performance when disabling it.

As Steve notes, this is not really a security feature.  Instead, it’s intended to be more a warning to users about which data is confidential and which is publicly-sharable .

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On-Prem Power BI Gateway

Published 2017-04-13 by Kevin Feasel

Steve Hughes shows how to set up a data gateway for Power BI:

First, I will not be discussing the personal gateway in this post. If you have chosen to use the personal gateway, you have limited functionality and should consider using the on-premises data gateway for corporate use.

The on-premises data gateway (referred to as gateway throughout this post) “acts as a bridge, providing quick and secure data transfer between on-premises data and the Power BI, Microsoft Flow, Logic Apps, and PowerApps services.” (ref) Much of what is discussed here will apply to all of the services referenced above, but our primary concern is related to Power BI. Please refer to references at the end of this post for details about data sources supported within the gateway.

Click through for more information.

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Power BI Quick Measures

Published 2017-04-12 by Kevin Feasel

Paul Turley has a post on the new “Quick measures” functionality in Power BI:

I had added the new Quick Measures feature to Power BI Desktop in the Options/Preview page.  This, apparently disables Quick Calcs and enables Quick Measures.  Although it flustered me me for a minute in front of an audience, I found this to be welcome news.  So, what is Quick Measures?  It’s a DAX calculation generator that automatically writes useful measures.  Here’s how it works…  Start by right-clicking or clicking on the ellipsis for a numeric column in the Field list and choose Quick measure…

The Quick measures dialog prompts for the necessary fields, which might be different for each calculation.  The tool generates appropriately formatted DAX calculations.  It even includes conditions to raise errors if used in the wrong context.  There are currently 19 different calculation variations that the tool will generate.  Following are two examples.  Creating a Quick measure from my [Flights] measure and choosing the Airline field for categorization produces this calculation:

Looks to be interesting.  Read the whole thing.

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Sharing Power BI Data

Published 2017-04-12 by Kevin Feasel

Steve Hughes is starting a series on Power BI security:

Another way to compartmentalize or secure data is using Workspaces within Power BI. Every user, including free users, have access to My Workspace which is the default location for deploying Power BI and other BI assets. However, you also have the option to create additional workspaces as deployment targets. These Group Workspaces usually have functional and security separation associated with them.

This post is a good overview of methods available for data sharing.

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R Plots In Power BI

Published 2017-04-11 by Kevin Feasel

Leila Etaati has a three-part series on displaying R visuals in Power BI.  Part 1 shows how to create a scatter plot:

so in the above picture we can see that we have 3 different fields that has been shown in the chart :highway and city speed in y and x axis. while the car’s cylinder varibale has been shown as different cycle size. However may be you need a bigger cycle to differentiate cylinder with 8 to 4 so we able to do that with add another layer by adding a function name

Part 2 shows how to use facet_grid to show multiple plots in one visual:

now I want to add other layer to this chart. by adding year and car drive option to the chart. To do that first choose year and drv  from data field in power BI. As I have mentioned before, now the dataset variable will  hold data about speed in city, speed in highway, number of cylinder, years of cars and type of drive.

I am going to use another function in the ggplot packages name “facet_grid” that helps me to show the different facet in my scatter chart. in this function, year and drv (driver) will be shown against each other.

Part 3 shows how to place charts on a map in R:

Now I have to merg the data to get the location information from “sPDF” into “ddf”. To do that I am going to use” merge” function. As you can see in below code, first argument is our first dataset “ddf” and the second one is the data on Lat and Lon of location (sPDF). the third and forth columns show the main variables for joining these two dataset as “ddf” (x) is “country” and in the second one “sPDF”  is “Admin”. the result will be stored in “df” dataset

Aside from my strong dislike of bar/pie charts on maps, this is good to know, particularly if there is not a built-in or customer Power BI visual to replicate something you can do in R.

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Network Navaigator Custom Visual

Published 2017-04-07 by Kevin Feasel

Devin Knight continues his Power BI custom visuals series:

In this module you will learn how to use the Network Navigator Power BI Custom Visual.  You may find the need to use the Network Navigator when you’re trying to find links between different attributes in a dataset. It does this by visualizing each attribute as a node and the strength of activity between those nodes can be represented in multiple ways.

Click through to get to Devin’s video.  This visual looks interesting for graphical analysis, like trying to tease out common connections or discovering dependencies.

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Converting To Local Time In M

Published 2017-03-30 by Kevin Feasel

Chris Webb shows how to convert a datetime from UTC to your local time zone using M:

Here’s a brief explanation of what the query does:

  • First it reads the times from the Excel table and sets the Time column to be datetime data type

  • It then creates a new column called UTC and then takes the values in the Time column and converts them to datetimezone values, using the DateTime.AddZone() function to add a time zone offset of 0 hours, making them UTC times

  • Finally it creates a column called Local and converts the UTC times to my PC’s local time zone using the DateTimeZone.ToLocal() function

There are some limitations to what it does, so you can’t convert to just any time zone while still retaining Daylight Savings Time awareness.

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Attribute Slicer

Published 2017-03-30 by Kevin Feasel

Devin Knight continues his Power BI custom visuals series:

In this module you will learn how to use the Attribute Slicer Power BI Custom Visual.  Using the Attribute Slicer you have the ability to filter your entire report while also being able to visibly see a measure value associated with each attribute.

Click through for the video as well as more details.  This looks like a very interesting way of integrating a slicer with some important metric, like maybe including dollar amounts per sales region and then filtering by specific regions to show more detailed analyses.

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Consuming Live Data Vs On-Prem Gateway

Published 2017-03-24 by Kevin Feasel

Gogula Aryalingam explains the difference between two Power BI features:

The question: “Why does it say ‘Consume live data sources with full interactivity’ as one feature while the other feature says ‘Access on-premise data using the Data Connectivity Gateways’, while it is obvious that if you need to connect to an on-premise data source to consume live data it has to be through a gateway?”

Okay, this is how I would explain this:

Read on for the explanation.

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