1.Announcing Lakebase Public Preview
Lakebase public preview, a SQL-first lakehouse built for performance.
Traditional databases struggle with scale, speed, and modern AI workflows. They sit siloed from analytics, making intelligent application development harder than it should be. Lakebase is a serverless, Postgres-compatible database, integrated directly into the lakehouse. Built for real-time feature serving, model interaction, and unified governance , it marks a quiet but significant shift in how data apps are developed.
https://www.databricks.com/blog/announcing-lakebase-public-preview
2. Change Takes More Than a Megaphone: Communicate, Experiment and Educate to Drive Transformation
Transformation demands more than speaking up: it requires communication, experimentation, and education.
Real AI adoption doesn’t go viral, it builds through strong ties, repeated exposure, and shared success. When people see value, they follow. The organizations winning with AI are the ones educating, experimenting, and elevating others.
https://www.snowflake.com/en/blog/change-transformation-communication-education-ai/
3. SQLMesh delivers 22x faster data transformation and 10x cost savings vs dbt Core™ on Snowflake
Sqlmesh outperforms dbt Core on Snowflake with 22x faster transformations and 10x lower costs.
SQLMesh reimagines how data is transformed on Snowflake. By replacing physical rebuilds with virtual environments, tracking changes at the column level, and eliminating redundant computation, it saves over $1M annually and frees up 311 hours of developer time each month.
4. The complete stream processing journey on FlinkSQL
The stream processing lifecycle, powered by FlinkSQL.
Grab rebuilt its stream processing stack, from Zeppelin notebooks to a shared FlinkSQL gateway, cutting query times by 80% and enabling pipeline deployment in under 10 minutes. A compelling look at how stream processing can be fast, collaborative, and production-ready.
https://engineering.grab.com/the-complete-stream-processing-journey-on-flinksql
5.Macroeconomics and the data industry
Understanding the economic undercurrents driving data work today.
Venture capital flows, shifting interest rates, and economic cycles ripple through every layer of the data world, reshaping tools, budgets, and even career paths. Understanding these forces is key to navigating rapid change and making smarter decisions as a data professional.
Note: I have provided links for informational purposes and do not suggest endorsement to you. All views expressed in this newsletter are my own and do not represent current, former, or future employer” opinions.
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