Part 9/12:
- Big Data & Spark: Replaced traditional data warehouses with data lakes and in-memory processing.
The current wave with generative AI resembles these shifts, promising to redefine manual, repetitive, and procedural tasks through hyper automation and end-to-end pipeline generation.
Anticipated Changes in Data Engineering and Work Practices
Looking ahead, the role of data engineers and developers will evolve:
End-to-End Automation: The emphasis will shift toward building, maintaining, and managing automated data pipelines.
Increased Use of Unstructured Data: Incorporating richer, real-time, and unstructured sources will become essential.