Power BI

Dynamically changing title names in Power BI

/ Mitchell Pearson / Leave a comment

Hey Everyone! I’m excited that I’m finally getting this blog done! Also, I’ve embedded the YouTube video below Smile

Also, in other news, after 8 years of blogging I finally decided to make some kind of logo, it’s a little unique but I like it! Especially how I was able to sneak the board game in there, because I love board games!

Original on Transparent

Figure 1 – New logo

Here is the video posted on YouTube if you want to watch the steps in action.

What is a Dynamic Title in Power BI?

The idea around a dynamic title is that the name of the title changes automatically to reflect any filters that may be applied. In the automated gif below, watch how the title name changes as I drill down into the chart visual.

DynamicTitles

Figure 2 – Dynamic title, animated gif

Creating Dynamic Titles in Power BI with SELECTEDVALUE() Function

Creating the dynamic title you saw in Figure 2 above requires a little DAX, not much. First, create a new calculated measure and give it a name, in the YouTube video I called this measure Dynamic Title. Then I used the following expression:

image

This is a simple expression which will return the name of the country if only one country exist in the filter context, if not, it will return the text “All Countries”. In this example I am navigating a hierarchy, therefore, I want the title name to change for each level of the hierarchy as new filters are being applied. The following screenshot is the completed code from the video:

image

Conditional Formatting in Power BI on the Title of a visual

The final step is to use the calculated measure on the visualization with the following steps, see animated gif for reference:

  1. Select visual and navigate to the formatting pane
  2. Find the title category and expand it.
  3. Click on the fx icon next to title
  4. Select field value for Format By
  5. Select your measure from the drop down list for Based on Field.
  6. That’s it!

As always, hope this post helped!

2_Conditional Formatting


ALL vs ALLSELECTED in DAX and Power BI Desktop

/ Mitchell Pearson / 2 Comments

Hey all! In my latest YouTube video  on DAX I discuss how ALLSELECTED can be leveraged in Data Analysis Expressions (DAX). This continues a series of YouTube videos in which I discuss various DAX functions and how to use them in Power BI Desktop.

Please feel free to check out my YouTube channel and subscribe Winking smile at https://www.YouTube.com/c/MitchellPearson

If you want to watch the video of this function explained, please take a look below:

ALLSELECTED function in DAX and Power BI Desktop

First, let’s look at the definition of ALLSELECTED, provided inside Power BI desktop when referencing the function:

image

ALLSELECTED: Returns all the rows in a table, or all the values in a column, ignoring any filters that may have been applied inside the query, but keeping filters that come from the outside.

What does this mean? Well, it means that it will essentially ignore filters coming from that visual but still respect filters coming from slicers and filters outside that visual (the outer query)! And yes, this is pretty awesome as you will soon see.

ALL vs. ALLSELECTED DAX functions

The biggest difference between ALL and ALLSELECTED is that the ALL function ignores all filters, regardless of where they are coming from. In contrast, the ALLSELECTED function only ignores filters that are coming from the inner query.

Returning Total Sales of all Selected Countries

The following expression in DAX would return the total sales for all countries in all scenarios. For example, the countries Australia, Canada and France were selected in the slicer, but yet the measure Total Sales All Countries still returns the total sales across all countries:

image

Figure 1.1

In this scenario, you might want to return Total Sales for all countries selected in the slicer (allselected), $13,682,863.16. This can be quite tricky, especially if you didn’t know of the existence of the ALLSELECTED function. Let’s write the expression in Figure 1.1 a different way and look at the results.
image

Figure 1.2

In this example you can clearly observe that ALLSELECTED is providing different way to analyze your data. I love this dynamic approach to analyzing data that is provided by simply modifying the ALL function to use ALLSELECTED!

As always, I hope this blog has helped someone somewhere and thanks for reading my blog!!

Using R in Power BI to check if file exist

/ Mitchell Pearson / Leave a comment

I have done a series of blog posts on how R can be used in Power BI. I have also created quick videos for each of those posts and I will do the same for this post. I find it easier and more efficient to share this information via video than through a narrative with screenshots. In this blog post, I’m going to share the code that can be used to check if a file exist prior to processing of that file. I will record a video that goes in more depth and include that in the blog post later.

Check if file exist

As someone who comes from an enterprise BI background, I am always looking for ways to handle things I would have previously done with SSIS. With R integration we have a lot of new possibilities.

The Code:

fileexists <- FALSE
fileName   <- “C:\\Backup\\Blogs\\R – Check if File Exist\\CustomerSales1.csv“

while (fileexists == FALSE)
    {
   #fileexists = TRUE ##Test Expression
   fileexists <-
            if(
                file.exists(fileName))
               {TRUE} else {FALSE}
   print(fileexists)
   ## Add 3 second Delay
   Sys.sleep(3)   
    }
   
    data  = read.csv(fileName)
    head(data)

PASS Summit–Lightning Talk on R

/ Mitchell Pearson / Leave a comment

I’m excited to have the opportunity to speak at PASS Summit 2018. I am doing a quick 10 minute lightning talk on R integration with Power BI. Somehow I was able to sneak in with this incredible group of speakers! SHHHHH, don’t tell anyone lest they find out!

Speakers

I have loaded my slide deck here, this includes what you need to get started with R! Slide Deck

In this talk I am focusing on how R can be used to extend the capabilities and functionality of Power BI. More specifically, I will be using R to show the following four demos:

  • How to extract data from Power BI using R
  • How to unzip and process files with R
  • How to Download, unzip and process files
  • How to check if file exist before processing the file

Also, I have created blog posts with corresponding YouTube videos already on 3 of the 4 demos listed above!

YouTube

My YouTube channel is simply MitchellSQL

Blog: MitchellPearson.com

Below are the three blog posts that I have previously posted:

Export Data from Power BI using R

Unzip and Process files into Power BI with R

Download, unzip, and process with R

2 things you need to know about Power BI Security

/ Mitchell Pearson / Leave a comment

In this blog post, I want to quickly discuss 2 things you need to know about Power BI Security as it relates to the Power BI Service. Many of the clients that I visit and perform training for are just getting into an implementation of Power BI and are not aware of these two items. I will probably come back and update this list as there are a couple more items I want to add, but those will take slightly more explanation! Smile

Publish to Web should be disabled

The publish to web feature provides an Iframe that allows a user to take a report and then embed that anywhere an Iframe can be accepted. The problem with this is that now the report is 100% security free and anyone who has access to the report has access to everything in it.

If you choose not to disable this feature it should, at the very least, be limited to specific people within the organization who have received proper training. To disable or manage this feature you must perform the following steps:

  • You must be a Power BI Administrator
  • Next, select Admin Portal from the settings wheel found in the Power BI Service.

image

  • From the admin portal, select Tenant Settings and then expand Publish to Web.
  • Click on the button to disable Publish to Web feature.

image

Direct Query to a relational database is not a RLS enabled data source

Many users, especially users on later versions of SQL Server, assume incorrectly that a direct query connection to SQL Server will use the security restraints applied at the database level. Unfortunately, this just isn’t the case.

Any user connecting to a report with Direct Query is using the stored credentials in the enterprise data gateway and therefore will have access to whatever the data gateway has access to. So if you have enabled row level security on the tables for your database, this is not going to work with direct query.

However, you can and should add row level security to your power bi data model (pbix) file. This row level security will work and limit access as it is intended!

Not sure how to set up Row Level Security in Power BI? Thanks ok! Click Here

Download and unzip files using R in Power BI

/ Mitchell Pearson / Leave a comment

In a previous blog, I wrote about how you could use R to unzip files. Well, that raises the question, can I download a zip file and then unzip it using R?

You can view the previous blog post on how to unzip files here.

Update: YouTube video can be found at the bottom of this post!

Download files using R

In general, downloading and processing a file can be done in Power BI very easily using “web” as the data source and you never have to worry about using R. However, if you need to do something more complex then R can be very helpful. For example, you may want to download a zip file, unzip it, and then process it.

In this example, I am going to download a zip file that contains names by state, this zip file is stored in the following location:

https://www.ssa.gov/oact/babynames/state/namesbystate.zip

This zip file has data for each of the different states, for this example I only want to look at the data for Florida. So we are going to unzip the file and only extract the data from the single file that we need data from.

Let’s take a look at the code in R Studio and break it down:

image

  1. First, I want to store the destination location and filename in a variable, this is done in lines 1-2.
  2. Next, I want to download the zip file and store it locally, this is done in lines 4-6.
  3. Thirdly, now the file will be unzipped and the file FL.TXT will be stored in the variable FLnames, lines 8-9.
  4. Lastly, we will read the text file and store it in the variable babynames.

The only thing we added in this example that was not in the previous blog post was the ability of downloading the code. If you, missed the previous blog and want to know how to import the data into Power BI, you can check that our here.

 

Thanks, for checking out my blog!

Using R to unzip and process files into Power BI

/ Mitchell Pearson / 4 Comments

There are a lot of blogs and videos out there on how to use R to enhance the visualization layer of Power BI. In this small series, I want to focus on how R can be used to improve the data importing and data cleansing capabilities of Power BI. Previously, I wrote how you could use the R language in Power BI to export data out to a CSV file. You can view that blog by following this link.

Update: Video embedded at bottom of blog post.

Although, I personally am not an expert when it comes to R, I’m learning more each day, it’s one of the topics I enjoy teaching the most in our Advanced Power BI Boot Camp.

Now it’s time for the required Pirate Picture: ARRRRRRRR. By the way, this image is from a tabletop game I like playing called Merchants & Marauders!!

Image result for pirate arrrrr

Getting Started with R in Power BI

To work with R you will need to have R installed. I use Microsoft R open, link provided below. You can optionally download R studio as well. Both of these are free downloads.

Required: Download the Microsoft R Open

Optional: Download R Studio

Discloser: At the time of this blog post, there is no built-in intellisense in Power BI to help write and debug R. Therefore, I use R Studio to write and test my code! R Studio is not a requirement, it is, in my experience, just very helpful.

UNZ and READ.CSV in R

The problem I want to solve in this blog post is how to unzip a file with Power BI and then process that file. Because I come from an enterprise BI background my first thought is to approach this problem with a tool like SSIS or PowerShell. However, there is an easier way, why else would we be here! Smile

I want to show you how you can use R to unzip and then extract data from a file all in one step. By the way, it’s really, really easy!

Let’s start off by looking at the code, this is all of it!:

image

  1. On line one, we are declaring a variable called data, this variable will store the results of our expression.
  2. On line two we are using read.csv to extract the results from the csv file, Customer Sales, and these results are stored in the variable from step one, please note that this process can not occur until after the file has been unzipped.
  3. On lines three and four we are using UNZ to unzip the file Customer Sale.zip and then return the file Customer Sales.csv.

And that’s it!

Wait, wait, wait…. What is line seven? Well, line seven allows me to test the results in R Studio. This is not needed for the importing data into Power BI Desktop. Oh, that reminds me, we need to import the data into Power BI Desktop!

Importing data using R in Power BI Desktop

As you are already aware, there are a lot of data sources available in Power BI, it shouldn’t surprise you that one of those data sources is R. Now let’s walk through how we can quickly import data from an R script into Power BI Desktop.

From the home ribbon in Power BI, click Get Data –> Other –> R Script. See screenshot below:

image

This will launch the R Script editor. As I previously mentioned, this script editor is simply a text box. Now we simply paste in our code from R studio, or if you happen to be an R aficionado you can just type your code in this box, as seen below:

image

Once we click ok, the Navigator window will open. Since we only declared one variable in our script, only one option will be provided. From here, everything is exactly the same as any other data source.

4_Navigator Window

Ok, now we’re done! I hope you enjoyed this blog post and I look forward to writing more, until next time.

Using Composite model with Dynamic Security in Power BI

/ Mitchell Pearson / 2 Comments

Like many others, I have not been an advocate of using Direct Query, it has long had many concerns diminishing its’ overall usefulness with one of the major key issues being performance. The Microsoft Power BI team has made major strides to mitigate the concerns around performance by adding two new key features: Composite Model and Aggregations. This blog will not discuss aggregations. However, we will briefly discuss the composite model and how we can use this to make Dynamic Security better.

The composite model simply allows users to import data and use Direct Query in the same data model. This has long been a point of contention for Power BI users because combining these two features into one model adds a lot of value. In this blog, I am going to briefly explain how this model helps to improve dynamic row level security.

I was sure I had previously blogged about dynamic row level security but I don’t see a post so I am going to re-direct you elsewhere. If you are interested in learning exactly how to implement dynamic security you can check it out here: Dynamic Security implementation

I am a huge advocate for Dynamic Security. Dynamic security allows you to create a single role in Power BI and then you can manage all your user security in a single table. Take a look at the following table which I am now storing in SQL Server:

image

So why would the composite model make dynamic security better?

Great question. Historically, I would always import data into Power BI, including the dynamic security table. The problem with this method is what happens with the security of the data if the model is not being refreshed? For example, I may reassign which users have access to which sales territories in my security table but if data models in the service are not being refreshed then the security is not being refreshed and thus users will have access to data they should not have.

Now, with the composite model I can still import all my reporting data but then I can set up a direct query connection to my dynamic security table. This means that all of Power BI models using this table will always be up to date!

image

Hopefully you can find many more useful scenarios for the composite model! Thanks for reading my blog!

Power BI Resources

/ Mitchell Pearson / 1 Comment

This blog post is a quick post to outline some of the resources around Power BI that I have found most useful, I will update this list accordingly.

Power BI Learning Tour

Brand new to Power BI? If so, this Microsoft led training is a great place to start:

https://docs.microsoft.com/en-us/power-bi/guided-learning/

Custom Visuals – Series by Devin Knight

Devin Knight has, at the time of this blog, recorded 117 videos on his blog dedicated to demonstrating different custom visuals created by the community. If you are not already aware of this blog series, take a look at the link below!:

https://devinknightsql.com/category/power-bi-custom-visuals/

PowerBI.tips – Custom Theme Generator

My personal favorite from powerbi.tips is the custom theme generator. They also have pre-built layouts, tutorials and many other valuable resources.

https://powerbi.tips/

DAX Guide

The DAX Guide is a great place to browse and explore available DAX functions.

https://dax.guide/

Have something that just has to be on this list? Let me know!

HASONEVALUE vs ISFILTERED in DAX

/ Mitchell Pearson / Leave a comment

I use the function HASONEVALUE quite often, many times it is in the context of solving problems with the total row. I wrote a blog on how to handle totals using HASONEVALUE here:

Unfortunately, HASONEVALUE is not always the tool for the job. For this scenario I am returning Homes Sold Month-to-Date. The final solution should look like the following screenshot:

image

As you can see in the previous image we want to return the Homes Sold MTD if we are at the day level or the month level, but if we are at a level higher than the month level then we simply want to return a blank value. It doesn’t make sense in this scenario to show MTD homes sold at the quarter or year level. If we use HASONEVALUE(‘date’[Date]) here, then no value is returned at the Month level. Here is an example:

image

As you can see in this example, a blank value is returned for the month of January. As previously mentioned the desired behavior is to return a value for the month of January.

IsFiltered

IsFiltered: Returns TRUE when columnName is being filtered directly. Else, False.

Let’s take a look at what IsFiltered returns if we are checking to see if the date is filtered:

image

ISFILTERED returns False for the month and Year as expected. Now, we can simply chain multiple IsFiltered functions together to return our desired results. In the following screenshot I added an or condition to check if the month was also filtered. As you can see, the results now return TRUE at the day and month level.

image

Now we can apply some conditional logic using the IF function based on the results of the IsFiltered expression in example above. If the day or month IsFiltered then return the MTD homes sold, else return BLANK(). See below:

image

Thanks for checking out my blog!