ETL vs ELT: two data integration methods for one strategic choice

Just one letter away from transforming the way you manage your data! On the one hand we have the Extract Transform Load team, on the other the Extract Load Transform team. Both are winners.

While both technologies are designed to transfer data from one place to another, each has its own characteristics.

“Whatever the choice, data teams are successfully implementing their integration strategies.”

As its name suggests, the #ETL method transforms the data before loading it onto the server, while the #ELT method transforms it afterwards. Doesn’t change much, you might ask? Well, it does! Depending on your business and your #data requirements, one solution may be more appropriate than the other. For example, the data ingestion process is slower with ETL because the data is transformed on a separate server before being loaded. On the other hand, ETL lends itself very well to data flows that require manipulation before entering a target system, reducing the risk of transferring non-compliant data. With ELT, on the other hand, the fact that data is not sent to a secondary server to be restructured offers teams greater responsiveness, as they can re-interrogate raw data to quickly develop new transformations.

Read the full article on journaldunet

Stay Ahead: Subscribe to Our Newsletter

Get Exclusive Updates and Offers Directly to Your Inbox. Join Our Community Today!

Similar Posts

Tech Recruitment: How to Attract Top Talent
Boosting Sales with an Effective CRM Strategy
The keys to successfully integrating Salesforce into your company
Skip to content