Data Engineering · Data Engineering

Databricks

This track covers Databricks' unified analytics platform: Lakehouse architecture, cluster management, notebooks, and Delta Lake. You'll learn to build and run ETL pipelines, optimize Spark jobs, and enable data quality. It's for data engineers and analysts who want to operationalize data workloads. You'll leave able to design multi-stage ELT workflows and govern data on the Databricks platform.

Start tutorial

Sponsored

Lesson outline

  1. 13
    Delta Lake Time Travel

    Learn time travel with Delta Lake in this Databricks tutorial — hands-on steps, troubleshooting, and what to study next.

  2. 14
    Optimize Delta Tables with Z-Ordering

    Learn how to optimize Delta tables with Z-ordering in Databricks. This hands-on tutorial covers the core concept, step-by-step implementation, and best practices to improve query performance on large datasets.

  3. 15
    Compact Small Files with OPTIMIZE

    Learn how to compact small files in Delta Lake using OPTIMIZE. This Databricks tutorial covers the problem, step-by-step execution, tuning options, and troubleshooting.

  4. 16
    Build a Simple Batch ETL Pipeline

    Learn to build a simple batch ETL pipeline in Databricks—hands-on steps, troubleshooting, and what to study next.

  5. 17
    Schedule Notebooks with Jobs

    Learn how to schedule notebooks with Databricks Jobs—set up automated runs, manage clusters, and troubleshoot failures for reliable ETL workflows.

  6. 18
    Parameterize Databricks Notebooks

    Use parameters to parameterize notebooks in Databricks — reduce duplication, run the same notebook for different inputs, and build reusable pipelines.

  7. 19
    Monitor Databricks Jobs

    Learn how to monitor Databricks jobs and view run history to track performance, debug failures, and optimize workflows in this hands-on tutorial.

  8. 20
    Set up access control for folders and tables

    Set up access control for folders and tables in Databricks. This tutorial covers the core concepts, step-by-step setup, hands-on exercise, troubleshooting, and next steps for securing your data workspace.

  9. 21
    Databricks CLI Secrets Management

    Learn to handle secrets with the Databricks CLI. This lesson covers the core concepts, step-by-step instructions, and troubleshooting for secure credential management.

  10. 22
    Databricks SQL Endpoints for BI

    Learn to use Databricks SQL endpoints for BI: create endpoints, connect to BI tools, manage concurrency, and follow a hands-on tutorial.

  11. 23
    Write Incremental Loads with Auto Loader

    Learn to write incremental loads with Auto Loader in Databricks. This hands-on tutorial covers the core concept, step-by-step implementation, troubleshooting, and next steps in the learning path.

  12. 24
    Inspect table metadata

    Learn to inspect lineage and table metadata in Databricks. This lesson covers how to view column-level lineage, see table properties, and use catalog explorer.

    Databricks — step-by-step tutorials

    What you will find here

    This track walks through databricks in order — each lesson is server-rendered HTML you can read without JavaScript. Follow the outline, then practice in the browser IDE when a lesson links to runnable code.

    Tutorials vs quizzes and code samples

    Tutorials teach in sequence. For quick checks use quizzes. For copy-paste snippets see code samples. For deeper reading browse articles.