Microsoft Fabric – Notebook and Data Wrangler

#fabric

Power Platform - General

The article discusses using Microsoft Fabric to work with Spark notebooks and Data Wrangler to transform data with minimal manual coding.
It provides a step-by-step guide on creating and renaming a notebook, adding a Markdown Title cell, loading a file into a data frame, and running a code cell.
The Data Wrangler tool is introduced as a way to automate data transformations such as renaming columns, changing column types, and dropping columns.
Instructions on adding Data Wrangler code to the notebook and running the code to see the transformed data frame are included.
The final step involves writing the data frame to a table using a specific line of code, saving it as a table called "Products" in the Lakehouse.
The article concludes by highlighting the usefulness of Data Wrangler in simplifying data transformation tasks within notebooks, comparing it to the Power Query tool for notebooks.
The author acknowledges the initial complexity of working with notebooks but emphasizes the value of tools like Data Wrangler for streamlining the process.
There is a mention of considering the use of notebooks versus dataflows based on the specific requirements of the data being handled.

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