Explore data analytics in Microsoft Fabric

In this exercise you’ll explore data ingestion and analytics in a Microsoft Fabric Lakehouse.

This lab will take approximately 25 minutes to complete.

Note: You’ll need a Microsoft Fabric license to complete this exercise. See Getting started with Fabric for details of how to enable a free Fabric trial license. You will need a Microsoft school or work account to do this. If you don’t have one, you can sign up for a trial of Microsoft Office 365 E3 or higher.

Create a workspace

Before working with data in Fabric, create a workspace with the Fabric trial enabled.

Sign into Microsoft Fabric at https://app.fabric.microsoft.com.
In the menu bar on the left, select Workspaces (the icon looks similar to 🗇).
Create a new workspace with a name of your choice, selecting a licensing mode in the Advanced section that includes Fabric capacity (Trial, Premium, or Fabric).
When your new workspace opens, it should be empty.

Create a lakehouse

Now that you have a workspace, it’s time to switch to the Data engineering experience in the portal and create a data lakehouse for your data files.

At the bottom left of the portal, switch to the Data Engineering experience.

The data engineering home page includes tiles to create commonly used data engineering assets.
In the Data engineering home page, create a new Lakehouse with a name of your choice.

After a minute or so, a new lakehouse will be created:
View the new lakehouse, and note that the Lakehouse explorer pane on the left enables you to browse tables and files in the lakehouse:
- The Tables folder contains tables that you can query using SQL. Tables in a Microsoft Fabric lakehouse are based on the open source Delta Lake file format, commonly used in Apache Spark.
- The Files folder contains data files in the OneLake storage for the lakehouse that aren’t associated with managed delta tables. You can also create shortcuts in this folder to reference data that is stored externally.
Currently, there are no tables or files in the lakehouse.

Ingest data

A simple way to ingest data is to use a Copy Data activity in a pipeline to extract the data from a source and copy it to a file in the lakehouse.

On the Home page for your lakehouse, in the Get data menu, select New data pipeline, and create a new data pipeline named Ingest Sales Data.
In the Copy Data wizard, on the Choose a data source page, select the Retail Data Model from Wide World Importers sample dataset.
Select Next and view the tables in the data source on the Connect to data source page.
Select the dimension_stock_item table, which contains records of products. Then select Next to progress to the Choose data destination page.
On the Choose data destination page, select your existing lakehouse. Then select Next.
Set the following data destination options, and then select Next:
- Root folder: Tables
- Load settings: Load to new table
- Destination table name: dimension_stock_item
- Column mappings: Leave the default mappings as-is
- Enable partition: Unselected
On the Review + save page, ensure that the Start data transfer immediately option is selected, and then select Save + Run.

A new pipeline containing a Copy Data activity is created, as shown here:

When the pipeline starts to run, you can monitor its status in the Output pane under the pipeline designer. Use the ↻ (Refresh) icon to refresh the status, and wait until it has succeeeded.
In the hub menu bar on the left, select your lakehouse.
On the Home page, in the Lakehouse explorer pane, expand Tables and verify that the dimension_stock_item table has been created.

Note: If the new table is listed as unidentified, use the Refresh button in the lakehouse toolbar to refresh the view.
Select the dimension_stock_item table to view its contents.

Query data in a lakehouse

Now that you have ingested data into a table in the lakehouse, you can use SQL to query it.

At the top right of the Lakehouse page, switch to the SQL analytics endpoint for your lakehouse.
In the toolbar, select New SQL query. Then enter the following SQL code into the query editor:
```
 SELECT Brand, COUNT(StockItemKey) AS Products
 FROM dimension_stock_item
 GROUP BY Brand
```
Select the ▷ Run button to run the query and review the results, which should reveal that there are two brand values (N/A and Northwind) and show the number of products in each.

Visualize data in a lakehouse

Microsoft Fabric lakehouses organize all tables in a semantic data model, which you can use to create visualizations and reports.

At the bottom left of the page, under the Explorer pane, select the Model tab to see the data model for the tables in the lakehouse (in this case there is only one table).
In the toolbar, select New report to open a new browser tab containing the Power BI report designer.
In the report designer:
1. In the Data pane, expand the dimension_stock_item table and select the Brand and StockItemKey fields.
2. In the Visualizations pane, select the Stacked bar chart visualization (it’s the first one listed). Then ensure that the Y-axis contains the Brand field and change the aggregation in the X-axis to Count so that it contains the Count of StockItemKey field. Finally, resize the visualization in the report canvas to fill the available space.
Tip: You can use the » icons to hide the report designer panes in order to see the report more clearly.
On the File menu, select Save to save the report as Brand Quantity Report in your Fabric workspace.

You can now close the browser tab contaning the report to return to your lakehouse. You can find the report in the page for your workspace in the Microsoft Fabric portal.

Clean up resources

If you’ve finished exploring Microsoft Fabric, you can delete the workspace you created for this exercise.

In the bar on the left, select the icon for your workspace to view all of the items it contains.
In the … menu on the toolbar, select Workspace settings.
In the Other section, select Remove this workspace.