Learn Databricks with End to End using PySpark, SQL & Delta Lake to build real ETL pipelines
What you'll learn
✓ Understand how Databricks is used in real-world data engineering
✓ Build ETL pipelines using PySpark and SQL in Databricks
✓ Work with large datasets using Spark DataFrames
✓ Perform data transformations, joins, and aggregations
✓ Use Delta Lake for reliable and scalable data pipelines
✓ Design end-to-end data engineering workflows
✓ Load, process, and analyze data using Databricks notebooks
✓ Gain hands-on experience by building a complete data pipeline project
✓ Build complete end-to-end ETL pipelines using Databricks
✓ Work with PySpark DataFrames for real-world data processing
✓ Use SQL in Databricks for filtering, joins, and aggregations
✓ Perform data transformations on large datasets efficiently
✓ Understand and use Delta Lake features like update, merge, and time travel
✓ Design scalable data engineering workflows
✓ Work with real-world datasets inside Databricks notebooks
Requirements
● Willingness to learn and practice hands-on data engineering concepts
● Basic understanding of SQL is helpful but not required
● No prior experience with Databricks is needed
● Basic programming knowledge is a plus (not mandatory)
● A laptop or computer with internet access
Description
Databricks is one of the most in-demand tools for modern data engineering, and in this course, you will learn how to use Databricks to build real-world ETL pipelines using PySpark, SQL, and Delta Lake.
This course is designed for beginners as well as professionals who want to gain hands-on experience with Databricks and understand how data engineering workflows are built in real-world scenarios.
We will start from the basics by setting up Databricks Community Edition and understanding the core components such as workspace, clusters, notebooks, and DBFS.
As you progress, you will learn how to work with data using PySpark and SQL, perform data transformations, and handle large datasets efficiently using Spark.
You will also learn about Delta Lake and how it helps in building reliable and scalable data pipelines.
By the end of this course, you will build a complete ETL pipeline where you will ingest raw data, clean and transform it, and create structured data for analytics.
This course focuses on practical learning with step-by-step demonstrations, making it easy to follow along even if you are new to Databricks.
If you want to start your journey in data engineering or upgrade your skills with modern tools like Databricks, this course is for you.
Who this course is for
■ Beginners who want to learn Databricks for data engineering
■ Data analysts looking to transition into data engineering roles
■ Data engineers who want hands-on experience with Databricks, PySpark, and Delta Lake
■ Students who want to build real-world ETL pipelines using modern tools
■ Professionals working with data who want to upskill in big data technologies
■ Anyone interested in learning how data pipelines are built in real-world projects


https://rapidgator.net/file/89157615753771fa58eee00e5ab613a5/Databricks_for_Data_Engineering_PySpark,_SQL_&_Delta_Lake.part1.rar.html,_SQL_&_Delta_Lake.part3.rar.html
https://rapidgator.net/file/28c7499749baee35296b615b6b6ce292/Databricks_for_Data_Engineering_PySpark,_SQL_&_Delta_Lake.part2.rar.html,_SQL_&_Delta_Lake.part2.rar.html
https://rapidgator.net/file/464abae04c526bc37406093f969a927b/Databricks_for_Data_Engineering_PySpark,_SQL_&_Delta_Lake.part3.rar.html,_SQL_&_Delta_Lake.part1.rar.html