CNBC is now accepting nominations for the 2026 Disruptor 50 list. Submit a nomination before February 23. Databricks said it is raising $4 billion at a $134 billion valuation to support AI app ...

This project demonstrates how to use Azure Databricks and PySpark to explore and transform financial transaction data. The provided lab notebook (banking_lab.dbc) contained a series of prompts guiding ...

Query groups uses AI to cluster similar search queries. The new card shows total clicks per group and highlights groups trending up or down. Query groups will roll out over the coming weeks to high ...

Enterprise AI keeps hitting the same wall - not enough people who know how to use it. Databricks is spending $10 million to fix that constraint in the UK, but the real question is whether vendor-led ...

Many enterprises running PostgreSQL databases for their applications face the same expensive reality. When they need to analyze that operational data or feed it to AI models, they build ETL (Extract, ...

Have you ever found yourself drowning in a sea of messy spreadsheets, spending hours manually cleaning and organizing data? For many Excel users, this is a frustratingly familiar scenario. But what if ...

Databricks Inc. says it’s trying to bring the power of big data analytics to every business worker with the launch of its new artificial intelligence-powered business intelligence tool, Databricks One ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire Apache ...

Forbes contributors publish independent expert analyses and insights. Peter Cohan, a Boston-based senior contributor, covers stocks. Before launching artificial intelligence agents, businesses want ...

Have you ever found yourself buried under a mountain of Excel sheets, each holding pieces of data that need to be stitched together into one cohesive whole? It’s a common challenge for anyone working ...

Today’s “big data stack” includes databases, data management and integration software, and data analytics tools—all critical components of an effective operational or analytical data system. But all ...