Create Your First Lakehouse & Load CSV, Parquet, JSON Files
Microsoft Fabric Tutorial
📘 What is a Lakehouse in Microsoft Fabric?
A Lakehouse in Microsoft Fabric combines the scalability and flexibility of a data lake with the structured querying power of a data warehouse. It stores files in Delta Lake format, enabling analytics directly over raw and structured data — using SQL, notebooks, or Power BI.
✅ What You'll Learn in This Tutorial
- What a Lakehouse is and its role in Microsoft Fabric
- Step-by-step process to create a new Lakehouse
- How to upload and manage CSV, Parquet, and JSON files
- How Microsoft Fabric unifies data lake and data warehouse capabilities
- Practical tips to structure your Lakehouse for analytics workloads
🛠️ Step-by-Step: Creating Your First Lakehouse
- Log in to Microsoft Fabric Portal
- Go to your workspace and click + New → Lakehouse
- Give your Lakehouse a name and hit Create
Once created, you'll land in the Lakehouse explorer which allows you to manage files, tables, and notebooks.
📂 Upload CSV, Parquet, and JSON Files
Inside your Lakehouse, switch to the Files tab:
- Click on Upload and select one or more files (CSV, Parquet, or JSON)
- Uploaded files are stored in
/Filesfolder - You can preview and open these files in notebooks or convert them into managed Delta tables
📊 Unifying Data Lake and Warehouse
Microsoft Fabric allows you to treat your Lakehouse like a warehouse using DirectLake and SQL endpoints:
- Run SQL queries on files/tables using SQL analytics endpoint
- Use Power BI for visualizations without importing data
- Query Delta tables using Spark notebooks
💡 Tips to Structure Your Lakehouse
- Use folders like
/raw,/processed, and/curatedto stage data - Convert CSV and JSON into Delta tables for analytics
- Tag or name files consistently: e.g.,
sales_2025_Q2.csv
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