Learn Together: Ingest data with Spark and Microsoft Fabric notebooks

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Discover how to use Apache Spark and Python for data ingestion into a Microsoft Fabric lakehouse. Fabric notebooks provide a scalable and systematic solution.

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Learning objectives

- Ingest external data to Fabric lakehouses using Spark
- Configure external source authentication and optimization
- Load data into lakehouse as files or as Delta tables

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Chapters
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00:00 - Introduction
05:49 - Learning objectives
06:22 - Context in Fabric
10:32 - What is Spark?
14:55 - An introduction to notebooks
16:43 - Explore Fabric notebooks
22:29 - What is a lakehouse?
25:45 - Fabric lakehouse vs Data warehouse
28:48 - Write data into a lakehouse
30:58 - Write to a Delta table
34:14 - Consider uses for ingested data
42:02 - Exercise - Ingest data with Spark and Microsoft Fabric notebooks
1:04:52 - Knowledge check
1:13:25 - Summary

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Presenters

Johan Ludvig Brattås
Director, Microsoft MVP
Deloitte

Heini Ilmarinen
Azure Lead, Microsoft MVP
Polar Squad

Moderators

Marcel Magalhães
Power BI Consultant, Microsoft Super User
G2M Consultoria e Treinamento


Olivier Van Steenlandt
Core Member, Microsoft MVP

[XLSavvy]

Tremendoudly Impressed With Notebook Experience in Fabric. Loved it.

[adilmajeed]

No Support for Recursion and Geospatial datatypes.

[juliekim]

The lakehouse has the Tables and the Files in the Fabric. What are they? The Tables is a data warehouse and the Folders is a lakehouse? The lakehouse has a data warehouse underneath.