Extract, Transform, Load (ETL) is a crucial data integration process that enables organizations to consolidate data from multiple sources into a unified data repository and derive actionable insights from them.
In the ETL process, data is extracted from various source systems, transformed to meet business requirements, and then loaded into a data warehouse for analysis and reporting. This flow is from operational systems to a centralized data repository. The primary goal of ETL is to consolidate and prepare data for analysis by transforming it into a structured format suitable for reporting and business intelligence.
Another process is Reverse ETL, which involves extracting data from a data warehouse and loading it back into operational systems or applications. This process pushes data downstream to where businesses can leverage analytical insights in real time.
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