Insights, tutorials, and best practices for modern data architecture and lakehouse implementation.
Master AWS data lakehouse architecture with expert guidance on service selection, governance models, and team readiness. Learn decision frameworks for cloud-native vs OSS formats, access controls, and compute models.
Your use case should drive your data lake platform choice, not vendor hype. Compare AWS Lake Formation's flexibility, Azure ADLS Gen2's enterprise governance, and Google BigLake's analytics speed to find your perfect match.
A comprehensive analysis of leading cloud data lake platforms, their 2025 innovations, and how to choose the right solution for your enterprise data strategy. Compare AWS, Azure, GCP, Databricks, Snowflake, and Cloudera.
Discover the evolution from data lakes and warehouses to the modern data lakehouse architecture. Learn how this unified approach combines the best of both worlds for scalable, cost-effective data analytics.
Explore the top five benefits of data lakehouses—performance, cost, flexibility, governance, and real-world use cases. Learn how to unlock these instantly with automation inspired by Starburst and Quest.
Break down the five essential layers of a modern data lakehouse—ingestion, storage, metadata, compute/API, and consumption. See how each maps to real cloud services and how automation makes deployment easy.
A deep dive into the differences between data warehouses, data lakes, and data lakehouses. Learn the pros and cons of each, and why a lakehouse is the modern answer—with best-practice automation.
From complexity to governance, here's how to navigate the hurdles and unlock the true power of your data lakehouse.
Discover how data lakehouses are becoming the ultimate unified playground for AI and ML, enabling everything from computer vision to large language models with diverse data types and real-time ingestion.