ETL and ELT are two different data integration approaches that involve moving raw data from a source system to a target database, such as a data lake or data warehouse. While they share ...

Basically, ETL just couldn’t keep up. With the introduction of data lakes and flexible storage schemas, big data changed the data warehouse landscape completely. Data lakes no longer required a ...

Data is optimized for business intelligence and analytics once it is loaded into a data warehouse after ETL. ETL processes can store historical data, which means businesses can perform trend ...

Your organization will continue to use the ETL tools that it’s familiar with, and the migration will get done faster. If you’re migrating a data lake or a data warehouse to the cloud ...

Reverse ETL is straightforward in function — move data from your data warehouse to your cloud applications. Reverse ETL tools synchronize data on a recurring schedule (configurable between a few ...

Although Internet companies feel they have no use for expensive, proprietary data warehouses, the fact of the matter is that ETL is still a requirement and so is some kind of a data warehouse. The ...

We’re also providing reverse ETL capabilities, which you can think of as a syncing back out of the data warehouse into all of the tools in that marketing and analytics stack, regardless of the ...

ETL is a process that has been around since the 1970s. It is used in data transformation to prepare it for storage and analysis in a data warehouse. It’s especially popular in business ...