Read, Clean, and Save Lakehouse to Delta Table Using Data Wrangler | Microsoft Fabric Tutorial for Beginners

Read, Clean, and Save Lakehouse to Delta Table Using Data Wrangler

Microsoft Fabric Tutorial

📘 What is Data Wrangler in Microsoft Fabric?

Data Wrangler is a powerful UI-based tool in Microsoft Fabric that allows you to explore, clean, transform, and prepare your data visually before saving it to a Delta table. It is built with data engineers and analysts in mind, allowing no-code or low-code data shaping before analysis or modeling.

✅ What You'll Learn

• How to launch Data Wrangler from your Lakehouse
• Read raw files (CSV/Parquet/JSON) into a temporary table
• Apply transformations such as filtering, renaming, changing data types, and cleaning nulls
• Save the cleaned dataset as a managed Delta Table in the Lakehouse

🛠️ Step-by-Step Instructions

1. Go to your Lakehouse workspace in Microsoft Fabric
2. Navigate to the Files tab and locate a CSV or Parquet file
3. Right-click the file and select Open in Data Wrangler
4. Apply transformations using the UI (you’ll see Spark/Python code generated)
5. Click Export to Lakehouse and choose to save as a Delta Table

🎯 Best Practices

• Preview your data to detect malformed rows before loading
• Use column profiling to check distributions and nulls
• Export frequently used clean datasets into Delta for better query performance
• Rename columns and fix data types early in the wrangling process

🎬 Watch the Tutorial Video

Blog created with help from ChatGPT and Gemini.