
Databricks notebooks | Databricks on AWS
Sep 3, 2025 · Notebooks are the primary tool for creating data science and machine learning workflows on Databricks. Databricks notebooks provide real-time coauthoring in multiple …
Develop code in Databricks notebooks | Databricks on AWS
Jan 8, 2026 · Develop code in Databricks notebooks, including code formatting, mixing languages, variable explorer, code modularization with files, and version history.
Basic editing in Databricks notebooks | Databricks on AWS
Nov 5, 2025 · A Databricks notebook is a web-based code editor that allows you to write code and view results for interactive data analysis. This page covers the basics of using notebooks in …
Manage notebooks - Databricks on AWS
Oct 2, 2025 · Learn how to create, open, delete, rename, and control access to Databricks notebooks using the Databricks UI, CLI, and Workspace API.
Tutorial: Query and visualize data from a notebook - Databricks
Feb 13, 2025 · This tutorial walks you through using a Databricks notebook to query sample data stored in Unity Catalog using SQL, Python, Scala, and R and then visualize the query results …
Run Databricks notebooks | Databricks on AWS
Oct 13, 2025 · Learn how to run a Databricks notebook. Learn about the notifications that appear.
Tutorial: EDA techniques using Databricks notebooks
Aug 8, 2025 · This tutorial guides you through the basics of conducting exploratory data analysis (EDA) in a Databricks notebook, from loading data to generating insights.
Customize notebook appearance | Databricks on AWS
Jul 2, 2025 · Learn how to customize your notebook appearance, such as adding line numbers and enabling dark mode, with various Databricks settings.
Software engineering best practices for notebooks - Databricks
Dec 17, 2025 · Learn how to apply software engineering best practices to your Databricks notebooks, including version control, code sharing, testing, and CI/CD.
Get started with AI agents - Databricks on AWS
Dec 9, 2025 · Now that you have an agent, you can package and deploy it to a Databricks serving endpoint. Start collecting feedback on a deployed agent by sharing it with others and chatting …