Microsoft Fabric Connections Demystified

Managing data connections in Microsoft Fabric can be challenging if you’re unsure where to start. This blog post and its detailed YouTube video will help you find, manage, and share the existing data connections, making your workflow more efficient and streamlined. A meaningful use case for this feature is to reuse the existing connections leading to more controlled connections to the data sources. More on this later in this blog.

Understanding Data Connections in Microsoft Fabric

In Microsoft Fabric, a data connection links the platform to various data sources, whether in the cloud or on-premises. Different items in Microsoft Fabric, such as Data Factory Pipelines, Dataflows, Paginated reports, Semantic Models, KQL databases, and Mirrored Azure SQL databases (currently in preview), create these data connections.

Finding Data Connections

To find data connections in Microsoft Fabric:

  1. Click on Settings at the top right of the page.
  2. Select Manage connections and gateways.
  3. Navigate to the Connections tab.

This tab displays all the connections shared with you or created by you. From here, you can check the status of each connection, remove old connections, and manage them as needed.

Manage connections and gateways in Microsoft Fabric
Manage connections and gateways

This page used to be called Manage Gateways where we could configure and manage on-premises data gateways. I have a very old blog post explaining the gateway setup and configuration in the cloud and on your local server here. While it’s an old post, the topics are still relevant, so check it out if you are interested in the gateway configuration.

Note

As the preceding image shows, the Data page is currently in public Preview, hence, it is subject to change. It is also worthwhile to mention that not all connections are currently accessible via this page such as connections that are natively created by KQL databases within Fabric.

Check Connection Status

To check the connection status, click the status button of each connection. The result shows if the connection is online or offline.

Check connection status
Check connection status
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Export Power BI Service Data to SQL Server

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Update 2021 March:

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.

To see the dataset settings:

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Power BI and SSAS Multidimensional

Update: If you are here to learn how to browse your SSAS Multidimensional model in Power BI please refer to this article. The current article shows you how to refresh data on Power BI service on top of a SSAS Multidimensional instance based on data import scenario.

It’s been a while that lots of us are waiting for seeing improvements on Power BI and SSAS Multidimensional. The good news is that Microsoft released a new version of Power BI Personal Gateway last week on 3 Sep 2015. One of the new features added to this release is that we can now refresh an on-prem SSAS Multidimensional model (data import scenario) after we published it to Power BI website. But, what data import scenario means? That means we cannot create mashups with data we already have in an existing SSAS Multidimensional database/cube through the SQL Server Analysis Services connector which is available on Power BI website. So we need to connect to a SSAS multidimensional instance through Power BI Desktop and load the cube’s data into the Power BI model. Indeed we will create a relational model on top a multidimensional model from SSAS.

Then we can create reports and publish them to Power BI website and finally we’ll be able to schedule data refresh on the Power BI website.

We can also connect to a SSAS Multidimensional instance through Power Pivot AND/OR Power Query from Excel then load the Excel file into Power BI website.

Note: We can do the same through Power Query, but, we won’t able to setup a data refresh schedule on Power BI website if we didn’t load

It’s just awesome isn’t it?

In this post I show you how to implement all the data import scenarios using Power BI Desktop, Power Pivot and Power Query from Excel.

First of all you need to download the gateway from here. Then you need to uninstall the existing version of Power BI Personal Gateway from your machine and install the new version. The whole gateway installation and process of refreshing an on-prem SSAS database is pretty much the same as what I explained in this post so I leave the installation part to you.  However, I explain the data refresh part again.

SSAS Multidimensional Data Import Scenario Through Power BI Desktop:

Get Data

  • Open Power BI Desktop
  • Click Get Data
  • Select “SQL Server Analysis Services Database” from the list and click “Connect”

Power BI and SSAS Multidimensional 01

  • Enter the SQL Server Analysis Services instance name
  • The database name is optional, but, I put “AdventureWorksDW2012”
  • Click “Select items and get data from Multidimensional or Tabular model”
  • As you can see you can also put your MDX or DAX custom queries, but, we leave it blank in our sample
  • Click OK

Power BI and SSAS Multidimensional 02

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MySQL and Power BI, How Does It Work?

MySQL and Power BI

Update 1: At the time of writing this blog post (Aug 2015) Power BI Service called Power BI Web. I hope it doesn’t make any confusions.

Update 2: MySQL data source is available in “On-premises Data Gateway – Enterprise Mode” as well. So if you are setting this up for an organisation, then “Personal Mode” (AKA Power BI Personal Gateway) would not be suitable. When I wrote this blog post only “Power BI Personal Gateway” was available.

In this post I explain how to use MySQL and Power BI. This post covers the following areas:

  • Get data from MySQL
  • Schedule refresh on-premises MySQL from power BI web app

First of all I’d like to mention that in this post I use AdventureWorksDW which is imported into MySQL. If you want to do so you can use “Migration Wizard” from “Database” menu on MySQL Workbench.

MySQL and Power BI

I’m not going to explain the migration process as it’s out of scope.

How MySQL and Power BI work together

MySQL is one of the world’s most popular relational database management systems (RDBMS) widely used by the industry. It’s open source, works with many different system platforms including Microsoft Windows and Linux. So it is worth to have a look at it and see how it works with Power BI.

Luckily Microsoft provided the built-in connector in Power BI Desktop. This is how it works all together:

MySQL and Power BI

I’d like to say that it’s not necessary to create reports in Power BI Desktop. You can get data from a MySQL database then publish it to the Power BI cloud then setup a schedule data refresh in the Power BI web app. Then you can create your reports and dashboards on the cloud and share them with your colleagues very easily.

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