Databricks co-founder Reynold Xin explains the limitations of traditional monolithic OLTP databases and introduces Lakebase, a serverless Postgres database that externalizes storage and compute. The a…
The Office for Students, England's higher education regulator, migrated to Databricks to modernize its data analytics, reducing a 300-million-record processing job from 8 hours to minutes and cutting …
A new analysis of serverless databases for AI applications finds that decoupling compute and storage is critical for cost efficiency and performance, with studies showing 38% average cost reductions a…
Databricks announced its Data Intelligence Platform is helping professional sports teams turn massive streams of player tracking data into competitive advantages, addressing the challenge of fragmente…
Daikin Applied Americas uses Databricks Genie Code to build consistent data pipelines at scale, implementing a MECE skill framework to enforce architectural standards and accelerate pipeline developme…
Dashboards are visual interfaces that aggregate key metrics and data visualizations from multiple sources into a single screen, enabling users to monitor performance against specific goals. Modern das…
Kythera Labs is building an AI-native healthcare strategy platform on Databricks that gives health systems access to expert intelligence by transforming 339 billion claims records into a trustworthy d…
Databricks has been positioned as a Leader in the Gartner Magic Quadrant for AI Platforms for Data Science and Machine Learning for the second consecutive year, achieving the highest placement in exec…
Databricks and NVIDIA launched Genesis Workbench, an open, governed life-sciences platform that integrates NVIDIA accelerated computing and BioNeMo models into Databricks environments for end-to-end d…
Agentic AI systems autonomously plan, execute, and adapt multi-step workflows to achieve specific goals with minimal human intervention, distinguishing them from traditional AI models that respond to …
A Databricks report based on 20,000 organizations reveals that AI business value clusters around specific use cases, with customer service and forecasting leading adoption. Companies succeed by priori…
Retrieval Augmented Generation (RAG) is an AI architecture that connects large language models to external knowledge sources at inference time, enabling accurate, context-aware responses beyond static…
Vector search is a technique that retrieves results based on semantic meaning rather than exact keyword matches, using embeddings to compare concepts across text, images, and audio. It powers modern A…
A new practical guide compares data lake and cloud data warehouse architectures for data scientists, outlining key differences in storage, cost, governance, and ML performance. The guide recommends da…
Data scientists are increasingly expected to work with large language models, build generative AI applications, and deploy models to production, expanding their role beyond classical modeling. The shi…
Data pipeline best practices for architecture, ingestion, transformation, and deployment are outlined, emphasizing the importance of defining SLAs and mapping pipelines to business requirements. Moder…
Artificial intelligence (AI) is a branch of computer science that enables machines to perform tasks requiring human intelligence, such as learning, reasoning, and pattern recognition. AI systems learn…
Data engineering is the foundational backbone of AI systems, requiring new architectural patterns and rigorous data quality to ensure model success in production. Data engineers now co-own reliability…
Payment fraud costs businesses over $100 million annually, driving banks, merchants, and fintechs to deploy machine learning systems that analyze hundreds of data points in milliseconds to block unaut…
An AI agent harness is the software infrastructure that wraps around a large language model to enable it to act on tasks, not just respond to prompts. The harness connects the model to tools, memory, …