In this Blog we are going to find out out What is ETL ,ELT and Which one is best approach ? But First Image ETL and ELT as Brothers of Which ETL is older One and ELT is Younger brother. Now What is ETL ?

  ETL i.e E for Extract, T for Transform, L for Load and It describes 3 different stages of a Data Pipeline.

So,Next Time If some one ask You know the Answer !! Similarly What is ELT ? Extract, Load, Tranform 3 different stages in a Data Pipeine.

Now What’s the difference Between ETL vs ELT ?

  1. For one thing, the transformations happen in a different order: Transformations for ETL pipelines take place within the data pipeline, before the data reaches its destination, whereas Transformations for ELT are decoupled from the data pipeline, and happen in the destination environment at will.
  2. They also differ in flexibility in how they can be used:ETL is normally a fixed process meant to serve a very specific function, whereas ELT is flexible, making data readily available for self-serve analytics.
  3. They also differ in their ability to handle Big Data:ETL processes traditionally handle structured, relational data, and on-premise computing resources handle the workflow.Thus, scalability can be a problem.ELT on the other hand, handles any kind of data, structured and unstructured. To handle scalability problems posed by Big Data, ELT leverages the on-demand scalability offered by cloud computing services.
  4. With regard to data discovery and time-to-insight:ETL pipelines take time and effort to modify, which means users must wait for the development team to implement their requested changes.ELT provides more agility. With some training in modern analytics applications, end users can easily connect to and experiment with the raw data, create their own dashboards,and run predictive models themselves. So, ELT is a natural evolution of ETL. Thus,You can say ELT is a winner here !! But It’s Not Winner Always There are use cases where ETL makes more sense.But That’s a discussion for different time.

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