Get Started With the “T” in ELT

Fivetran has released Transformations, making it a full-fledged ELT tool that allows users to extract, load and transform data in the same environment. The two main purposes of transforming data are for legibility and organizational coherence, similar to Looker's approach to models, and to enhance the performance and cost characteristics of your data warehouse. There are two methods for transforming data: views, which are not stored on disk and materialized views, which are stored on disk due to their better performance. Fivetran Transformations uses the materialized views approach by constructing new tables and updating them on a schedule chosen by the user. The transformation layer in Fivetran can be used for various tasks such as revising, cleaning, computing, separating, and integrating data.