Part 2/10:

Mishra begins by emphasizing the importance of high-quality and well-governed data in any successful data product. Traditionally, data pipelines involve close collaboration between data engineers and data analysts, often characterized by iterative cycles of requirement gathering, development, verification, and rework. This approach, while effective, presents notable challenges:

• Bottlenecks for Data Engineers: They are often bogged down in minor transformations, code modifications, and back-and-forth communication, limiting their capacity to focus on complex engineering tasks and system scalability.