Defining analytics engineering
We have seen in the previous section that with the advent of the modern data stack, data movement has become easier, and the focus has therefore switched over to managing raw data and transforming it into the refined data used in reports by business users. There are still plenty of cases where ad hoc integrations and ETL pipelines are needed, but this is not the main focus of the data team as it was in the past.
The other Copernican revolution is that the new data stack enables data professionals to work as a team, instead of perpetuating the work in isolation, which is common in the legacy data stack. The focus is now on applying software engineering best practices to make data transformation development as reliable as building software. You might have heard about DevOps and DataOps.
With this switch of focus, the term analytics engineering has emerged to identify the central part of the data life cycle going from the access to the raw data up...
