Naresh Govindaraj

This is the second post in a series where we discuss data architectures and the continued need for scalable and efficient data engineering. In the first post, we talked about the evolution of data architectures and how data teams are looking for a scalable and modern data solution that can address the needs of today […]

There has been a transition of data architectures from traditional ETL (Extract, Transform, Load) to a more modern ELT (Extract, Load, Transform) approach. This shift to profile and transform data using an ELT approach has been fueled by the migration to the cloud as businesses can now benefit from large-scale compute, near-infinite storage, higher return on investment, and lower total cost of ownership using the cloud.