Updated 27 Aug
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Learn Databricks
Learn how to use Databricks, PySpark, and Delta Lake to build modern data pipelines. Go from basic setup to creating and analyzing scalable data workflows using the Lakehouse architecture.
4.7
16 lessons
2h
Created by Educative
Join 3.1 million developers at
What You'll Learn
- Understand the Lakehouse architecture and how it improves upon traditional data lakes and warehouses.
- Navigate and use Databricks notebooks to run Python and SQL workflows.
- Create, inspect, and transform data using PySpark DataFrames.
- Work with Delta Lake to write, read, and manage reliable data tables with versioning.
- Build an end-to-end data pipeline from raw data ingestion to final analysis using SQL and PySpark.
Learning Roadmap
1.
Introduction to Databricks and Lakehouse
Introduction to Databricks and Lakehouse
Understand why Databricks is used and explore the Lakehouse architecture for unified data analytics.
2.
Setting Up Databricks
Setting Up Databricks
Learn how to sign up, explore the interface, and create your first notebook.
3.
PySpark Basics in Databricks
PySpark Basics in Databricks
4 Lessons
4 Lessons
Explore DataFrame creation, inspection, transformation, and reading CSVs using PySpark.
4.
Delta Lake Fundamentals
Delta Lake Fundamentals
3 Lessons
3 Lessons
Understand Delta Lake, how to read/write Delta tables, and use time travel features.
5.
SQL in Databricks
SQL in Databricks
2 Lessons
2 Lessons
Explore querying and managing Delta tables using SQL.
7.
Wrap Up and Next Steps
Wrap Up and Next Steps
2 Lessons
2 Lessons
Summarize real-world Databricks applications and key takeaways from the course.
Certificate of Completion
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Complete more lessons to unlock your certificate
Developed by MAANG Engineers
Trusted by 3.1 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
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