Databricks Data Science & Engineering user guide
This guide provides information about the tools available to you in the Databricks Data Science & Engineering workspace, as well as migration and security guidance.
- Databricks runtimes
- Data Science & Engineering workspace
- Clusters
- Notebooks
- Jobs
- Libraries
- Repos for Git integration
- Requirements
- Enable Repos
- Configure your Git integration with Databricks
- Create a repo and link it to a remote Git repository
- Work with repos
- Manage permissions
- Control access to repos with allow lists
- Secrets detection
- Repos API
- Best practices for integrating repos with CI/CD workflows
- Limitations and FAQ
- Troubleshooting
- Databricks File System (DBFS)
- Connect BI tools to Databricks clusters
- Migration
- Databricks security guide
- Enterprise security for the E2 version of the Databricks platform
- Access control
- Secret management
- Credential passthrough
- Credential redaction
- Customer-managed keys for managed services
- Customer-managed keys for workspace storage
- Secure cluster connectivity
- Encrypt traffic between cluster worker nodes
- IP access lists
- Configure domain name firewall rules
- Best practices: GDPR and CCPA compliance using Delta Lake
- HIPAA-compliant deployment
- Best practices: Data governance