Part 5/14:
The Modern Data Stack: Components and Challenges
The modern data stack generally comprises several interconnected layers:
Data ingestion from multiple sources
Storage in data lakes or warehouses
Data transformation and modeling
Cataloging with lineage tracking
Visualization and analytics
Orchestration and automation
While a powerful concept, assembling this stack traditionally involves multiple open-source tools—each managed independently—that can introduce challenges such as long deployment times, siloed teams, and fragile pipelines prone to breakdowns. Fragmented tools complicate coordination, reduce agility, and extend time-to-market for analytics solutions.