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.
Technology is growing fast and we are enjoying it. We reshape our daily created data in a form that satisfies our needs. One of the technologies which is used more commonly these days is SQL Server Tabular Models, SSAS Tabular in short. Lots of industries decide to go with SSAS Tabular in their new projects and some defined new projects to slowly switch their existing SSAS Multidimensional to SSAS Tabular. I know, there is a big debate around SSAS Multidimensional vs. SSAS Tabular. But my aim is to prevent going through that sort of discussion. As the title implies, this post is about documentation that I believe is one of the most important parts of every project which is also sacrificed the most. In this post I explain how to document your SSAS Tabular model in Power BI Desktop and Excel. I know, there are some products you can find in the internet that can generate documentation in various formats like Word, PDF, HTML and so on. But, If you’re looking for a free and somehow more intuitive way of documenting your SSAS Tabular Models with Power BI then this article is for you. Through this article, we create a documentation tool with Power BI. I call it SSAS Tabular Model Documenter. In this method we don’t use DMVs at all. For those who are not familiar with DMVs I shortly explain what DMVs are, if you’re already familiar with DMVs you can jump this section.
You can download a copy of SSAS Tabular Model Documenter in Power BI template format (pbit) at the end of this post. It is a Christmas present for you.
What are DMVs?
Dynamic Management Views, DMVs in short, are queries that retrieve metadata information about an instance of SQL Server Analysis Services. DMVs work on both SSAS Multidimensional and SSAS Tabular server modes. DMVs can be used to monitor server operations and health. The DMV query structure is very similar to T-SQL, therefore you use “SELECT” statement followed by “$System” which is an XMLA schema rowset. The DMV queries look like below:
SELECT * FROM $System.<schemaRowset>
So you can open SQL Server Management Studio, connect to an instance of SSAS (Tabular model for the sake of this post) and run the following query to get lots of information about tables in your Tabular model:
Note:This method only works with SSAS Tabular 2016 and above.
Document SSAS Tabular without DMVs
In SSAS Tabular 2016 and above there is a tiny metadata database that can be loaded in Power BI Desktop or Excel to document the corresponding SSAS Tabular model. The database is a SQLite database. In the previous post I explained how to visualise SQLite data in Power BI. The requirements for this post are the same as the previous post, so I encourage you to check it out. Therefore, I just explain how to find the metadata file and how to build a model in Power BI Desktop. I also explain how to do the same in Excel for those of you who would like to add some annotations or comments to the outcomes.
NOTE: This method is no longer available (from 1st March 2019) as Microsoft discontinued supporting Web Designer in Azure portal. Microsoft is working on an alternative solution, but there is no timeframes or details to announce yet. Read more here. In the meantime, you still can import your Power BI Desktop Models to SSAS Tabular following the method described here.
A while ago I wrote a blog post on how to import you currently existing Power BI Desktop models to SSAS Tabular 2016. However, the method I explained is NOT supported by official Microsoft BI tools like SSDT, so you may consider it as a WORKAROUND only until Microsoft supports imploring Power BI models in SSDT. In this post, I show you how to import Power BI Desktop Model to SSAS Tabular 2017 using Azure Analysis Services. It is easy and hassle free.
Requirements
Power BI Desktop: Make sure you have the latest version (Current Version: 2.52.4921.581 64-bit (November 2017))
Azure Subscription: You need to install an instance of Azure Analysis Services. Don’t worry about the costs, you can create an Azure free account with $200 credit for 30 days. Learn more here.
Notes:
In this post I do NOT explain how to install Azure Analysis Services
This method works only for SQL Server Analysis Services 2017 Tabular
How it works
As mentioned earlier it is really easy in compare with other methods I explained in my previous post. Azure Analysis Services is capable of importing Power BI Desktop files creating a Tabular model version of your Power BI model in the cloud. Then you can simply download Visual Studio project file and redeploy it in your on-premises instance of SSAS Tabular 2017. Let’s go through the steps…
Open Power BI Desktop
Import data from WorldWideImportersDW from any desired combination of fact tables and dimensions. I imported
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.)
