Get Started with Databricks for Data Engineering - French
This course introduces the foundational skills needed to perform a basic data engineering workflow on the Databricks Data Intelligence Platform. You will explore the workspace, work with Unity Catalog, and learn the day-to-day building blocks a data engineer uses on Databricks.
The course follows a hands-on path. You start by getting oriented in the workspace, then work through paired Demo and Lab notebooks for each topic. Demos walk you through a concept with the instructor or a guided notebook.
The content covers:
• The Databricks Data Intelligence Platform and how the Databricks workspace, Unity Catalog, and notebooks fit together.
• Creating and managing Delta Lake tables.
• Modifying data with INSERT, UPDATE, and DELETE.
• Exploring version history and time travel on Delta tables.
• Ingesting data with Lakeflow Connect options: CTAS, the Upload UI, and COPY INTO.
• Building a Medallion Architecture pipeline that transforms data through Bronze, Silver, and Gold layers.
• Automating pipelines with Lakeflow Jobs.
• (Bonus) Building a declarative pipeline with Spark Declarative Pipelines.
• Connaissance de base des plateformes de données cloud. Vous comprenez, sur le plan conceptuel, ce qu’est une base de données, une table et une requête.
• Maîtrise pratique de SQL. Vous savez lire et écrire des instructions SELECT avec WHERE, GROUP BY et des agrégations, et vous comprenez INSERT, UPDATE et DELETE.
• Une connaissance générale des concepts d’ingénierie des données, tels que l’ingestion, la transformation et les pipelines, est utile mais pas obligatoire — le cours couvre les bases.
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Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos
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