ETL Part 2 - Transformations and Loads — 1 user / 1 year

ETL Part 2 - Transformations and Loads — 1 user / 1 year

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In this course data engineers apply data transformation and writing best practices such as user-defined functions, join optimizations, and parallel database writes. By the end of this course, you will transform complex data with custom functions, load it into a target database, and navigate Databricks and Spark documents to source solutions.


2-4 hours, 75% hands-on


The course is a series of seven self-paced lessons available in both Scala and Python. A final capstone project involves writing custom, generalizable transformation logic to population data warehouse summary tables and efficiently writing the tables to a database. Each lesson includes hands-on exercises.

Supported platforms include Databricks Community Edition, Azure Databricks and Amazon.

Learning Objectives

During this course you:

  • Apply built-in functions to manipulate data
  • Write UDFs with a single DataFrame column inputs
  • Apply UDFs with a multiple DataFrame column inputs and that return complex types
  • Employ table join best practices relavant to big data environments
  • Repartition DataFrames to optimize table inserts
  • Write to managed and unmanaged tables



    1. Course Overview and Setup
    2. Common Transformations
    3. User Defined Functions
    4. Advanced UDFs
    5. Joins and Lookup Tables
    6. Database Writes
    7. Table Management
    8. Capstone Project: Custom Transformations, Aggregating and Loading

    Lab Requirements

    License Limitations

    This self-paced training course may be used by 1 user for 12 months from the date of purchase.  It may not be transferred or shared with any other user.


    The use of the self-paced training course is subject to the Terms of Service and the Databricks Privacy Policy.