Tag: SQL Server Data Tools

Azure Analysis Services, BISM Tabular, Power BI, Power BI Desktop, SQL Server Analysis Services - SSAS, Uncategorized

Import Power BI Desktop Model to SSAS Tabular 2017 Using Azure Analysis Services

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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

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
  • Create some simple Measures like:

Total Sales = SUMX(‘Fact Sale’, ‘Fact Sale'[Unit Price] * ‘Fact Sale'[Quantity])

  • Save your Power BI Model and close the file
  • Login to your Azure PortalBrowse to your instance of Azure Analysis Services
  • Click on “Open” under “Web designer—preview”

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  • This opens a new page for fabulous “Azure Analysis Services Web Designer”. You’re right, a web designer for tabular models. How cool is that? Smile
  • Click “Add” button under “Models” section
  • Yes, you got it, enter a name for your model and click “Power BI Desktop” button
  • Click “Browse” and select the Power BI file you saved earlier then click “Import”

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Power BI, Power BI Desktop, SQL Server, SQL Server 2016, SQL Server Analysis Services - SSAS, SQL Server Integration Services - SSIS, T-SQL, Uncategorized

Exporting Power BI Data to SQL Server

Exporting Power BI Data to SQL Server

Update 2021 March:

You can now export the data directly from Power BI Desktop using our free external tool, Power BI Exporter. Read more here.

Update 2019 April:

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. Smile 

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.

Library folder in R

Library folder in SQL Server 2016

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.)

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Azure, Azure SQL Data Warehouse, SQL Server 2016, SQL Server Management Studio - SSMS, T-SQL

Query Azure SQL Data Warehouse in SSMS and SSDT

Azure SQL Data Warehouse in SSMS and SSTD

A while ago I wrote a blog post about Azure SQL Data Warehouse and Power BI which I explained how to install a new instance of Azure SQL Data Warehouse and how to visualise your Azure SQL DW data in Power BI. In this post I explain how to query an Azure SQL DW in SSMS and Visual Studio.

Requirements

Querying Azure SQL Data Warehouse from Visual Studio

Prior the latest release of SQL Server Management Studio (SSMS) 2016, the only available tool for querying an Azure SQL Data Warehouse was SQL Server Data Tools (SSDT) for Visual Studio 2013 or 2015. Here is how you can use SSDT 2015 to query an Azure SQL Data Warehouse:

  • Open SQL Server Data Tools 2015
  • Click “SQL Object Explorer” from View menu

SQL Server Object Explorer Visual Studio

  • Click “Add SQL Server”

Add Server to SQL Server Object Explorer Visual Studio

Connect to Azure SQL Data Warehouse in SQL Server Object Explorer Visual Studio

  • Enter “Server Name”
  • If you don’t recall server name then open a web browser and log into Azure portal
  • Click “SQL databases”
  • Click any desired Azure SQL Data Warehouse you created before. Make sure the database is “Online”

Azure SQL Data Warehouse in Azure Portal

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SQL Server

Installing SQL Server 2014 CTP1

  • After downloading the SQL Server 2014, mount the media file downloaded and run “setup.exe”
  • In SQL Server Installation Centre click on “Installation”

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  • Click on “New SQL Server stand-alone installation or add features to an existing installation”

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Note that if you have any of previous versions of SQL Server installed on your machine the setup process will fail because this release of SQL Server cannot be installed in until the existing instances of SQL Servers are uninstalled.

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If you click on “Failed” you can read the complete error message that is “Previous SQL product installation failed. A SQL product other than SQL Server 2014 CTP1 is detected. You cannot install this release until the existing instances of SQL products are uninstalled.”

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