In this blog, we outline the essential steps for migrating ETL workloads and EDW from Snowflake to Databricks. From data migration to report modernization, we break down five key phases for a seamless and efficient transition to Databricks.

This blog explores why companies are increasingly migrating from Snowflake to Databricks, highlighting Databricks’ integrated platform, cost-efficiency, and comprehensive data and AI capabilities. The post examines the pitfalls of Snowflake's pricing and its struggle to replicate Databricks' functionality.

This blog compares Microsoft Fabric and Databricks, focusing on pricing, features, governance, and scalability. It concludes that while Fabric suits smaller businesses, Databricks excels for medium to large enterprises due to its flexibility, innovation, and advanced data capabilities.

Migrating to Databricks offers companies unmatched benefits, including cost efficiency, scalability, and advanced AI/ML capabilities. With a unified platform and robust data governance, Databricks empowers businesses to modernize their data estates, ensuring they’re future-ready and positioned for growth.

This blog argues against the rush to adopt the latest AI technologies, emphasizing the importance of strong data engineering foundations and "Classic Analytics." It advocates for a balanced, pragmatic approach to AI adoption, ensuring long-term success over short-term gains.

This article provides an initial analysis of Microsoft Fabric, comparing it with Databricks. It discusses why Fabric may not meet enterprise needs and explores potential integrations between Fabric and Databricks, highlighting how they can complement each other in data projects.