Discover how a modern data platform unifies data, boosts business intelligence, and drives decisions with real-world fintech and ecommerce examples.

A comparison of AWS, Google Cloud, and Azure for data platforms — from storage and processing to analytics, governance, and MLOps. How each shapes architecture, operations, and long-term flexibility.

Modern data engineering isn’t about building pipelines — it’s about building trust, reliability, and cost-aware systems. This article reframes the role and explains what experienced engineers actually do.

Parquet, ORC, Arrow, Delta, Iceberg, and Hudi — not just file formats, but architectural levers. Storage layout, compression, and schema semantics define how data moves, scales, and fails across distributed systems.

Learn how to manage the machine learning lifecycle with MLOps. Follow a fintech team’s journey to build, deploy, and monitor a fraud detection model, ensuring scalability and GDPR compliance.

Explore the 4 types of analytics—descriptive, diagnostic, predictive, prescriptive—and learn how they drive business decisions with real-world examples.