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Microsoft Fabric – Connecting Power BI to Fabric Lakehouse

Power BI update

Introduction to Microsoft Fabric 

Microsoft Fabric, the latest craze in the data space. But what is the big deal about it and how can we use it? Microsoft Fabric is a comprehensive platform designed to seamlessly integrate data storage, processing, and analytics. It’s not just another tool; it’s a tapestry that weaves together the worlds of data lakes and data warehouses, creating what is often referred to as a “Lakehouse.” Imagine having a single, unified space where your data flows effortlessly, and insights emerge with minimal fuss. 

We can leverage this powerful capability using Power BI as we are able to connect Power BI Desktop to a Fabric Lakehouse. This means, if there are various data sources you are using for your Power BI report, you now only need to connect to one source, Fabric Lakehouse, to start your reporting! In this blog post we take the first step in how we can do this. 

What is a Lakehouse

A Lakehouse blends the best of both data lakes and data warehouses. A Lakehouse is essentially a fusion of the flexibility of data lakes and the performance of data warehouses. It combines the raw, unstructured storage capabilities of a data lake with the structured, query-optimized processing of a data warehouse. This means you get the best of both worlds – the ability to store vast amounts of diverse data in its native format while still enjoying the speed and efficiency of structured querying. Picture it as a harmonious marriage, where lakes and warehouses coexist to create a versatile ecosystem for your data.

How we can use it with Power BI

Pre-requisites

  • Microsoft Fabric trial account 
  • Power BI 

For this section we will practically go through the steps one can take to connect Power BI with Microsoft Fabric’s Lakehouse. First thing you’ll need to do is create a Fabric trial account. 

Ingesting data into Microsoft Fabric

The next step would be to ingest some data. First you will need to sign into Fabric. You should immediately be taken to the home page.

Microsoft Fabric Homepage
Fig 1: Fabric home page

We need to ingest data into Fabric, to do this we need to utilize the Data Factory functionality. Data Factory is Fabric’s tool to ingest data using data flows or pipelines. It allows for cloud-scale data movement and data transformation services that can be used for complex data factory or ETL scenarios.

Creating a workspace in Microsoft Fabric

After we’ve selected Data Factory, we need to create a workspace to store our Lakehouse and other data we might need. Select the workspaces option in the far-left pane and select “New Workspace”.

Fabric storage page
Fig 2: Create new workspace.

Creating a Lakehouse in Microsoft Fabric

Once we have created our workspace, we need to create a Lakehouse for our data. Navigate to the drop-down button labelled “New”, on the top left corner of the widget and select “Lakehouse”. Follow the prompts to create your Lakehouse.

create lakehouse
Fig 3: Create new Lakehouse in your workspace.

Using a Pipeline to ingest data into our Lakehouse

For this step, we will use data already available to Fabric. We will ingest New York City taxicab data (you can download the parquet file here. However, Fabric already has this dataset available for you) using a pipeline in Fabric. Select the “New” drop-down menu as before, but this time, instead of selecting Lakehouse, select “Data Pipeline”. 

Select the “NYC Taxi – Green” sample data (as seen in figure 4). Follow the prompts and make sure to place your recently created Lakehouse as the data destination. 

nyc data
Fig 4: Ingest the NYC Taxi – Green dataset into your Lakehouse using a data pipeline.

Once this step is completed you should have a copy of the data in your workspace. Navigate over to your Lakehouse again, refresh the Tables and you should see the NYC Taxi dataset ready to be used!

Creating a semantic model for Power BI

We now need to share this data with Power BI (and with potential collaborators). To do this we need to create a new semantic model. This option you can see in the top ribbon in your Lakehouse. Select this option and select the dataset you want to use in Power BI.

create semantic model
Fig 5: Create new semantic model in your Lakehouse that will be visible to Power BI

Click confirm. After the semantic model is created, we can open Power BI Desktop, select the OneLake data hub drop-down menu on the top ribbon and select “Power BI datasets” (make sure the credentials you are using in your Power BI are the same credentials you are using in your Fabric account). A list of data options will appear, select the semantic model you had previously created and click connect. It’s as simple as that! You have now connected your Power BI to your Fabric Lakehouse and can start building your Power BI reports. 

select semantic model in powerBI
Fig 6: Select newly created semantic model using the OneLake data hub option in Power BI

Conclusion

Microsoft Fabric is a powerful platform that will only grow in popularity over the coming years. In this post we’ve only scratched the surface of how Power BI can be integrated and used with Fabric. We’ve discussed how to create a workspace in Fabric, how to create a Lakehouse in that workspace, how to ingest data into a Lakehouse using a data pipeline and then we’ve discussed how to connect Power BI to the data in our Lakehouse.

By understanding the process of ingesting data into Fabric and then connecting it to Power BI we’ve already got stuck into this cutting-edge technology and have been equipped with valuable knowledge.

To learn more about how Fabric can be used to add value to your organisation, visit our Microsoft Fabric Page. [Microsoft Fabric from Data Bear]

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