Get started articles, tutorials, and best practices

Databricks documentation includes many tutorials, Get started articles, and best practices guides.

Get started articles vs. tutorials

Get started articles provide a shortcut to understanding Databricks features or typical tasks you can perform in Databricks. Most of our Get started articles are intended for new users trying out Databricks.

Tutorials are slightly more complex, prescriptive steps for typical workflows in Databricks that you can use as examples for your projects.

Video tours

• Video: Databricks Data Science and Engineering workspace

• Video: Databricks SQL workspace

• Video: Databricks Machine Learning workspace

• Video: Notebook basics

Get started with Databricks Data Science & Engineering

• Get started: Query data from a notebook

• Get started: Build a basic ETL pipeline

• Tutorial: Run an end-to-end lakehouse analytics pipeline

• Tutorial: Build an end-to-end data pipeline

Get started with Databricks Machine Learning

• Get started: Databricks Machine Learning in-product quickstart

• 10-min tutorials: ML notebooks

• Get started: MLflow quickstart notebooks

Get started with Databricks SQL

• Databricks SQL user quickstart: Import and explore sample dashboards

• Databricks SQL user quickstart: Run and visualize a query

Best practices for Databricks

The Databricks documentation includes a number of best practices articles to help you get the best performance at the lowest cost when using and administering Databricks.

Data science and engineering best practices

• Delta Lake

• Hyperparameter tuning with Hyperopt

• Deep learning in Databricks

• Delta Lake Structured Streaming with Amazon Kinesis

• CI/CD

• MLOps worflows

Best practices for Databricks admins

• Cluster configuration

• Pools

• Cluster policies

• Data governance

• GDPR and CCPA compliance using Delta Lake