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A pipeline may include filtering, normalizing, and dataconsolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. Step 1- Automating the Lakehouse's data intake.
For this reason, there are various types of data integration. The key ones are dataconsolidation, data virtualization, and data replication. These types define the underlying principles of integrating data. Dataconsolidation. How dataconsolidation works.
A company’s production data, third-party ads data, click stream data, CRM data, and other data are hosted on various systems. An ETLtool or API-based batch processing/streaming is used to pump all of this data into a data warehouse. The following diagram explains how integrations work.
A pipeline may include filtering, normalizing, and dataconsolidation to provide desired data. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. Step 1- Automating the Lakehouse's data intake.
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