DATA WAREHOUSE – ETL/ELT

What is the ETL / ELT?

ETL or ELT is not a software abbreviation. It is the most important and complex stage of the data warehouse. ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are processes used to move data from one system to another (data sources to the data warehouse). These systems feed a process labeled ETL for “extracting, transforming, loading”.

 

ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are processes for moving data from one system to another (data sources to a data warehouse).(These systems feed a process labeled ETL for “extract, transform, load.”

This process consolidates information from the various operational systems, integrates it, and loads it into a single repository called the enterprise data warehouse.)

In short, it is called all of the stages where data goes through certain processes from the source to the target.

 

The steps of the ETL / ELT processes are as follows;

Extract: The process of getting data from source is also called performing the ETL first step.

Transform: The process of transforming the data received from the source with Extract. It is the step where operations such as data cleansing or data restriction are performed.

Load: The process of loading the transformed data is called load.

 

 

 

You can perform ETL / ELT processes as follows. By preparing packages with T-SQL or PL / SQL, you can perform import, transform and load data warehouse from this source. Another possible situation is that we can use ETL / ELT data. The most important example of these tools is Microsoft’s SSIS application. For Oracle, Data Integration (ODI) tools are very popular.

 

ELT process is the process that directly transfers data to the data warehouse without any transformation. Transform operation is used optionally. You can either convert after uploading, or use the source data directly. Cloud technologies are generally used in ELT processes. ELT process is a more modern system. New technologies, especially cloud technologies, allow the use of big data tools. But it still continues to develop.

 

The differences between ETL and ELT can be by the following situations.

  • Storage technologies
  • Design approach to data warehouse
  • Need for work

So, The subject has very detailed contents. This topic will not be complete with this article alone. It may be necessary to work in this particular area. It is the daily operations of employees in this field. You can contact me for more detailed questions.

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