Step 1: Sign in to Microsoft Fabric
Go to Microsoft Fabric and sign in with your credentials.
Step 2: Create a New Lakehouse
Click on the My Workspace, it will appear empty initially since we haven’t created any workspace yet.
Click the ellipsis (⋯) and Select "Create"
Under Data Engineering Click on "Lakehouse" and give your Lakehouse a name. In my own case i named my Lakehouse "SUBBYLAKEHOUSE" Click the "Create button" to create your Lakehouse.
Lakehouse is Successfully Created
Step 3: Upload Data into the Lakehouse
Click the ellipsis (⋯) at the front of (Files) Select **"Create a Subfolder" **under files.
Give your Subfolder a name, In my own case i'm naming my subfolder "DATA". Click on the "Create button".
Subfolder is successfully created
Click the ellipsis (⋯) at the front of Subfolder (DATA) Cick on Upload ** and Click on **upload files. i'll be uploading an **Amazon csv dataset **from my local Machine.
Select your file. in my case i'll select the file name "Amazon Sales dataset" the file is in .csv format.
Click on the Upload button to upload the Amazon Dataset into the subfolder.
Amazon dataset file is succesfully uploaded into Lakehouse.
Click on the Amazon Sales dataset to view raw dataset.
Step 4: Load Data into the into Table
Click the ellipsis (⋯) at the front of "DATA" Click on Load to table Click on New table.
Give your table a name. I'll name my table "Amazon" select my file extension which is ** .csv ** from the drop-down and Click on the "Load"
The Amazon table is created succesfully under Table.
Click on Amazon to view table.
Step 5: Query Data Using SQL
Data can be query in table using SQL or Pyspark. i'll be using SQL to Query data in the table.
Click on the drop-down and select SQL Analytics Endpoint
Click on New Query to start writing SQL Syntax to Query your dataset.
Conclusion:
By implementing this end-to-end lakehouse solution in Microsoft Fabric, I've successfully unified raw data storage with powerful analytics capabilities on a single SaaS platform. This project demonstrated how to:
🏗️ Create and configure a lakehouse
📥 Ingest structured and unstructured data
🔍 Query datasets using both SQL and Spark
🛠️ Build an integrated analytics environment
The Microsoft Fabric lakehouse architecture proves its value by eliminating traditional data silos while providing the flexibility of a data lake and the performance of a data warehouse. This foundation now enables more advanced scenarios like real-time analytics, machine learning, and business intelligence - all within one collaborative workspace.
Top comments (0)