You can now export the data directly from Power BI Desktop using my tool, Power BI Exporter. Read more here.
Update 2019 April:
If you’re interested in exporting the data model from Power BI Service to SQL Server check this out.
A while ago I wrote a blog post explaining how to Export Power BI Data to SQL Server with R. In that post I explained how to get the job done in Power BI Desktop using R scripts. In this post I explain how to export Power BI Service data to SQL server. YES! You can export data from Power BI service to a SQL Server database sitting in your on-premises environment. Keep reading to see how.
How It Works?
This is going to be a short post as I already covered the first part of the process in my other post on Export Power BI Data to SQL Server with R. So in this post I show you how to use the Power BI Desktop file you already created using the method explained in that blog post to export your Power BI Service data to an on-premises instance of SQL Server. All you need to do is to
Publish the existing Power BI Desktop solution to Power BI Service
Install On-premises Data Gateway in PERSONAL MODE
Note: R is NOT supported by the current version (Version Number: 14.16.6614.5) of the On-premises Data Gateway in Enterprise Mode.
After you successfully published the model to Power BI Service you’ll notice that you cannot refresh the model if you don’t install the On-premises Data Gateway in Personal Mode.
I recently spoke in Tampa Dev Azure Meeting in a webinar form on 31st Jan 2018. We received interesting questions during the presentation. My aim was to introduce basic concepts of Big Data, Azure Data Lake, Azure Data Lake Store (ADLS), Azure Data Factory (ADF) and Power BI.
I would like to thank Tampa Dev organisers and all attendees for giving the opportunity to speak in this session.
If you want to export the data model from either Power BI Desktop or Power BI Service to CSV or SQL Server check this out.
In the previous blog posts, I explained how to export Power BI data to Excel and CSV here and here. As promised in this post I explain how to export data from Power BI Desktop to SQL Server.
Hans Peter Pfister has already explained how to export data from Power BI Desktop to SQL Server using R scripts. Although Hans has done a brilliant job, it might be a bit hard to make it work if you don’t have any R experience and you don’t even know how to install and call R libraries. That’s so true about me, I’m NOT an R guy, but, who knows, maybe I will be.
But, what if you don’t want to go with R? If you are more involved with BI than analytics, then using R might not really be your cup of tea. Luckily, there is another way to export your Power BI data to SQL Server which is more BI friendly. You can export Power BI data to SQL Server using SSIS (SQL Server Integration Services). So if you are familiar with SSIS, then it might be your preferred choice.
With respect to Hans, in this post, I explain his method of exporting data from Power BI Desktop to SQL Server more in detail so that anyone who is not that familiar with R can make it work. I also explain how to export data from Power BI Desktop to SQL Server using SSIS. If there is any other methods you’re aware of please let me know in the comment section below.
Exporting Data from Power BI Desktop to SQL Server with R
As stated before, Hans has already explained this method here. So I don’t explain exactly what he did, but, I use his method to export data from the existing Power BI Desktop model to SQL Server and I explain it step-by-step.
Requirements
To make this method work you need to:
The latest version of Power BI Desktop, you can download it from here
Have access to an instance of SQL Server, either on your own machine or on a server in your local network to export the data to
Either install R for Windows, you can download it from here OR using an existing R-Server OR install SQL Server 2016 R Services
Install RODBC library for R, you can download the library from here
Note: I haven’t installed R Studio and nothing went wrong.
Installing RODBC Library for R and SQL Server R Services
As mentioned earlier, you can install R OR SQL Server R Services OR R-Server, but, as I haven’t tried R-Server myself I just explain how to install RODBC in R and SQL Server R Services.
You have to download the library from the link provided above, then extract the contents of the zip file which contains an “RODBC” folder. Then all you really need to do is to copy the “RODBC” to the “library” folder that exists in either R or SQL Server 2016 folders in your “Program Files” folder.
How Does It Work?
Open an existing Power BI Desktop model that you’re willing to export its data to a SQL Server table and follow the steps below: (I use the “Internet Sales” model created on top of AdventureWorksDW. You can download my Power BI Desktop model at the end of this post.)
A while ago I was working on a Power BI project which the customer wanted to define a new table directly in the model. The easiest way to achieve this in Power BI Desktop is to “Enter Data” which creates a new table by typing or pasting in new contents. I was thinking of that project the other day and thought, hey, how we can do the same in SSAS Tabular when there is no Power Query (M) language available in SSAS Tabular 2016. The good news is that Power Query will be available in the next version of SSAS Tabular in SQL Server vNext. But, until then a workaround would be entering data to a CSV file then load it to the model. Another way is to implement custom tables in DAX in SQL Server 2016 Tabular models using Table and Row Constructors. In this post I show you a way of creating custom table in SSAS Tabular using table constructors in DAX. You can do the same in Power BI as the same principle applies. Therefore, in case you’d prefer not to use “Enter Data” feature which effectively uses Power Query to create a new table in Power BI Desktop, then you can use DAX to do the same.
If don’t already have SQL Server 2016 it’s probably time to download and install it. I use AdventureWorksDW as sample database in this article.
Scenario
You are involved with an SSAS Tabular project and the customer asked for a report in Power BI with dynamic Card so that the values shown in the Card visual should dynamically change based on selected measure from a slicer. You have several different measures in the model and the customer wants to show some of them dynamically in only one Card visual. Consider you have the following measures to be shown in the Card:
Total Internet Sales
Internet Sales in 2014
Total Number of Internet Sales Transactions
You have to create a logic so that the users can selected any of the above measures to show in a single Card visual.
How it works
After you meet the requirements, you’re good to start implementing the above scenario in SQL Server Data Tool (SSDT). Creating a calculated table in SSAS Tabular 2016 is fairly easy. All we need to do is to create a custom table with two columns. One column stores friendly names for measures and the other one holds DAX expressions for the measures. As you might have noticed, I’m talking about creating a custom table in DAX and populating it with values. Continue reading to see how. What we are going to do is to create a calculated table using table constructors in DAX. Table and Row Constructors weren’t available in previous versions of DAX in SSAS Tabular. They are very similar to Lists or a list of Tuples just like what we have in MDX.
I’ll explain this later when we created our sample model in SSDT.
