Cross-organizational data sharing has a problem most teams do not talk about. Most of it still runs on workarounds. Scheduled exports to S3, FTP transfers with shared passwords, replicated datasets that are already stale before the recipient runs a single query. These approaches are brittle, ungoverned, and nearly impossible to revoke once the data is out. Databricks Delta Sharing was
Data teams have spent years stitching together separate tools for ingestion, transformation, storage, and reporting, each with its own compute model, governance approach, and billing cycle. The result is a coordination problem, and every team pays that tax constantly. Microsoft built Fabric to collapse that stack into a single experience, and data engineering is where that shift is felt most
92% of Fortune 500 companies use ChatGPT products as of 2026, and ChatGPT Enterprise message volume has grown 8x year-over-year. That adoption story started with employees using ChatGPT for individual tasks. It has since moved to engineering teams building directly on the OpenAI API, embedding model capabilities into products, internal tools, and automated workflows at scale. According to Gartner, more
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