Exploring data ingestion and processing

The process of obtaining and importing raw data for immediate use, processing, or storage is known as data ingestion.

To build an analytical environment, we use data ingestion techniques to copy data from sources and store it within a data lake or an analytical database; this process is called a data pipeline.

Data ingestion pipelines are composed of one or more steps of data processing, that is, a dataset of the data source is captured and processed, and then the output dataset is generated.

Data pipelines

Data pipelines load and process data through connected services, allowing you to select the best technology for each phase of the workflow.

For example, in Azure, you can use a SQL Server as a data source, then use Azure SQL Database to run a store procedure that searches for data values, and then run a processing routine with Azure Databricks by applying a custom data model. All of these are steps in a data pipeline.

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