ETL- The next gen working with data transformation

07-02-2019  0 Comment(s)

ETL stands for Extract, Transform and Load. ETL is one of the main components in a BI Solution backed by a Data Warehouse. ETL is also used in other projects like Data Migration and Data Integration projects. ETL flows/jobs can be built by scripting or by using ETL Tools. Most of the companies currently use one of the existing ETL tools to build ETL flows/jobs.

In short, ETL tools abstract the technical complexity and thereby enables developers to focus on ”what needs to be done” than on “how it needs to be done”, For example a developer doesn't have to bother about developing a connector to a Database, Developers design the ETL flow/Job using drag and drop, click and configure GUI of the ETL Tool and also run, test, debug, schedule the ETL Jobs using GUI of the ETL Tool.

ETL Tools provide a visual framework for ETL developers to design the ETL Jobs. It provides a level of abstraction of the code/script. There are many features that ETL tool provides but I won’t go in those details here.

ETL Tool allows the ETL Developers to focus on the Business logic/rules instead of the technical implementation. So, ETL developers focus on what to implement than on how to implement.

ETL Tool is expected to create optimized code for an ETL flow and is expected to either bring the data to the ETL server or perform operations in the Databases based on whichever is better for performance reasons. Ideally ETL developers shouldn't have to optimize the code but only configure the jobs/transformations/tool correctly such that optimized code is created for every ETL flow.

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