Data Integration

ETL or ELT? The question that probaly arise when you want to start your Data Integration process.

ETL (Extract Transform Load) is an integration approach that pulls information from remote sources, transforms it into defined formats and styles, then loads it into databases, data sources, or data warehouses.

ELT (Extract Load Transform) similarly extracts data from one or multiple remote sources, but then loads it into the target data warehouse without any other formatting. The transformation of data, in an ELT process, happens within the target database. ELT asks less of remote sources, requiring only their raw and unprepared data.

ETL and ELT have a lot in common. At their core, each integration method makes it possible to move data from a source to a data warehouse. The difference between the two lies in where the data is transformed, and how much of data is retained in the working data warehouse.

How we can help

We can help you designing the ETL / ELT process that you want to build in your Data Integration process based on the data condition in your environment, with the help of our Data Engineers that have experiences in many Data Integration projects, from designing a simple ETL process from / to RDBMS, to designing complex ELT process that involving Big Data as the data sources or data targets.

Industries

All businesses that need an extra hand to help them finish the Data Integration process that are running, or Businesses that want to start their new Data Integration journey involving new data sources or new technology that they just deployed.