This section provides a guide to developing notebooks in the Databricks Data Science & Engineering and Databricks Machine Learning environments using the SQL language.
If you are a data analyst who works primarily with SQL queries and BI tools, Databricks SQL provides an intuitive environment for running ad-hoc queries and creating dashboards on data stored in your data lake. You may want to skip this article, which is focused on developing notebooks in the Databricks Data Science & Engineering and Databricks Machine Learning environments. Instead see:
SQL notebooks support various types of visualizations using the
In addition to Databricks notebooks, you can also use various third-party developer tools, data sources, and other integrations. See Databricks integrations.
This article describes how to use SQL constructs to control access to database objects: