Developing Extract–transform–load (ETL) workflow is a time-consuming activity
yet a very important component of data warehousing process. The process to
develop ETL workflow is often ad-hoc, complex, trial and error based. It has
been suggested that formal modeling of ETL process can alleviate...
ETL refers to extract, transform, load and it is generally used for data
warehousing and data integration. ETL is a product of the relational database
era and it has not evolved much in last decade. With the arrival of new
cloud-native tools and platform, ETL...
Data integration generally requires in-depth domain knowledge, a strong
understanding of data schemas and underlying relationships. This can be
time-consuming and bit challenging if you are dealing with hundreds of data
sources and thousands of event types (see my recent article on ELT architecture
[https:...
A case for ELT (i.e. extract, load, and transform) and difference between ETL and ELT