Here is what you will learn as part of this chapter:
- Building the Gold Layer
- Tips and Tricks of DBSQL Dashboards
- Safe and Secure Sharing in the Databricks Marketplace
- Integrations for Insights
Here are the technical requirements needed to complete the hands-on examples in this chapter:
- We will use Databricks SQL, DBSQL Dashboards and Data Warehouses
- We utilize a Python package, opendatasets, to download the data we need from the Kaggle API with ease: https://pypi.org/project/opendatasets/
In the chapter
Further Reading
- MLFLow Model Registry Webhooks on Databricks
- Databricks SQL Statement Execution API
- Power to the SQL People: Introducing Python UDFs in Databricks SQL
- Actioning Customer Reviews at Scale with Databricks SQL AI Functions
- Databricks sets the official data warehousing performance record
- Databricks Lakehouse and Data Mesh