7 posts
The problem with "just add more workers" Most Spark performance issues on Databricks aren't solved by scaling the cluster — they're caused by shuffle and skew, ...
Most ML teams are great at training models. Very few are great at shipping them. The gap between a notebook that works and a model that reliably serves producti...
> A deep dive into the medallion architecture, Delta Lake internals, Z-ordering, and optimized Spark writes — the patterns that separate hobby projects from pro...
If you're building a data platform on Azure in 2026, you're going to be asked this question: Azure Databricks or Microsoft Fabric? Both run on Delta Lake, both ...
Azure Databricks doesn't live in isolation. In most enterprise Azure environments it sits downstream of Azure Data Factory, which orchestrates ingestion from da...
Batch pipelines are predictable. They run, they finish, you check the results. Streaming pipelines are alive — they never stop, failures compound, and a small m...
If you've ever spent more time debugging broken Spark jobs than actually building pipelines, Databricks Delta Live Tables (DLT) is worth your attention. Instead...