How do I convert and ingest data to Delta Lake on Databricks?
To convert and ingest data to Delta Lake on Databricks, you can use several methods and tools provided by Databricks. Here are some options:

1. **Delta Live Tables**: This is a managed service for building and deploying reliable data pipelines on Databricks. It simplifies ETL workloads through optimized execution and automated infrastructure deployment and scaling.

2. **Auto Loader**: Auto Loader is a built-in tool for incrementally loading data from cloud storage into Delta Lake. It automatically manages the file handling and monitoring, making it easier to ingest data.

3. **COPY INTO**: This SQL command allows you to load data from files into a Delta table. It provides options for handling schema evolution, data types, and error handling.

4. **Add data UI**: Databricks provides a user interface for adding data to your workspace. You can use this interface to upload files, connect to data sources, and create tables.

5. **Incrementally convert Parquet or Iceberg data to Delta Lake**: You can use the `convertToDelta` command to convert existing Parquet or Iceberg tables to Delta Lake tables without rewriting the data.

6. **One-time conversion of Parquet or Iceberg data to Delta Lake**: If you have existing Parquet or Iceberg tables, you can convert them to Delta Lake tables using the `convertToDelta` command.

7. **Third-party partners**: Databricks has partnerships with several third-party data integration tools that can help you load data into Delta Lake.

For more detailed information and examples, you can refer to the "Converting and ingesting data to Delta Lake" section in the provided documentation.