From the Blog
What we have learned building and tuning data platforms — written for the engineers and leads who have to run them.
AI Data Engineering: Why Your AI Project Is Really a Data Project
What AI data engineering means in practice — AI-ready data layers, chunking and embeddings, semantic layers for NL-to-SQL, evaluation sets, and the failures that kill AI pilots.
Read articleDatabricks Lakehouse Architecture: What Actually Matters in Production
A practical guide to medallion architecture on Databricks — bronze, silver, gold layers, Unity Catalog governance, job compute, and the mistakes that cost the most.
Read articleHow to Cut Your Snowflake Bill Without Slowing Anyone Down
A practical checklist for Snowflake cost optimization: warehouse sizing, auto-suspend, incremental dbt models, clustering, and cost attribution that actually holds up.
Read articleLet's talk about your data platform
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