Key features of the Databricks Snap Pack
Databricks is a cloud-based data platform with many open source components. It is available on all three major cloud providers i.e. Microsoft’s Azure, Amazon Web Services and Google Cloud.
Databricks allows data scientists, engineers, and analysts to collaborate. And with Databricks Snap Pack, you can automate use cases such as:
- Feeding big datasets from a variety of application and data endpoints for training ML models to solve problems such as demand forecasting, fraud detection, anti-money laundering, and so on.
- Preparing data for deep learning so as to harness the power of unstructured data for AI, image interpretation, automatic translation, natural language processing, and more.
- Delivering data to drive business insights through a faster, easy to use and scalable Data Lakehouse
- Feeding real-time data from sensors and other IoT endpoints for up-to-date insights.
Databricks Snap Pack contains the following snaps:
- Select: Retrieves information from the target Databricks table.
- Insert: Inserts new rows of data in the target Databricks table.
- Delete: Deletes data from a target Databricks table.
- Bulk load: Loads millions of rows of data in the target table
- Unload: Unloads data from a target Databricks table
- Merge into: Updates existing rows & inserts new rows in target table
- Multi-execute: Runs multiple SQL statements on the target Databricks instance
To learn more please refer to the documentation link: Databricks Documentation
