Part 6/11:
This complexity has led to heightened demands for speed, agility, and raw data access. Consumers increasingly prefer to work directly with raw datasets, reducing reliance on pre-aggregated or heavily transformed data. As a consequence, the traditional ETL process’s role is being redefined.
Is ETL Becoming Obsolete?
Given these industry shifts, many question whether the traditional ETL paradigm is still relevant. The speaker notes that ETL, which originated around the early 1970s, has been a backbone of data management for roughly 50 years. However, with the advent of cloud computing, real-time data needs, and self-service analytics, the notion of "slow" batch processing appears increasingly incompatible with business agility.