Send data to Databricks¶
Databricks provides a unified platform for data and AI that supports large-scale processing for batch and streaming workloads, standardized machine learning lifecycles, and accelerated data science workflows for large datasets.
Many organizations use Databricks to enable data scientists, engineers, developers, and data analysts within their organization to use data, along with a combination of Databricks SQL, R, Scala, and/or Python, to build models and tools, and to consume data through the interface you’re most comfortable with.
You can make data available to Databricks using any of the following cloud-based workflows:
after which you can connect Databricks to any of those external locations or use the data in a Databricks Delta table to build advanced round-trip SQL queries and to build models against your data.
Access this data using Databricks SQL or by connecting external data visualization tools like Tableau, Domo, or Looker to Databricks using a JDBC connection.
All workflows that make data available to Databricks should be configured to update automatically on a daily (or weekly) schedule. This ensures that users in your organization who will work in Databricks always have access to the latest data.