What is the process of connecting to a source, querying to create a dataset, and making it available for analytics called?

The process described in the question focuses on connecting to a data source, executing queries to generate a specific dataset, and preparing that dataset for subsequent analysis. This is characteristic of batch ingestion data flow.

In batch ingestion, data is collected over a defined period and processed collectively. This method is well-suited for scenarios where immediate data availability is not critical, allowing for efficient processing of large volumes of data at once.

Typically, this involves establishing connections to databases or data lakes, executing extraction queries to pull relevant data, and then organizing that data in a structured format suitable for analytics applications. This procedure is foundational for building analytics platforms, where timely and structured data plays a crucial role in generating insights and driving decision-making.

Other choices do not encapsulate this defined process as effectively. For instance, real-time streaming refers to continuous data input, which differs fundamentally from the batch method. Data analysis flow suggests the processes involved in analyzing data rather than preparing it for analysis. Meanwhile, the data transformation process primarily involves modifying data into a different format or structure, which is a subset of the broader ingestion process but not the complete pipeline from source connection to readiness for analytics.