Trusted Data for the Data Intelligence Platform: Databricks Ventures Invests in Anomalo
Reliable, accurate and trusted data is the most critical requirement for any data application in an enterprise. As Databricks customers increasingly rely on...
Databricks Announces the Industry’s First Generative AI Engineer Learning Pathway and Certification
Today, we are announcing the industry's first Generative AI Engineer learning pathway and certification to help ensure that data and AI practitioners have...
Data + AI Strategy: People Focus
This post is part of a series. Check out Part 1: The Data + AI Trifecta: People, Process, and Platform In the current...
Building and Customizing GenAI with Databricks: LLMs and Beyond
Generative AI has opened new worlds of possibilities for businesses and is being emphatically embraced across organizations. According to a recent MIT Tech...
Databricks SQL Year in Review (Part I): AI-optimized Performance and Serverless Compute
This is part 1 of a blog series where we look back at the major areas of progress for Databricks SQL in 2023...
Generative AI for retailers: driving top-line growth through skills development
Since COVID, countless articles have been written about the "Great Resignation", including in-depth analysis by the World Economic Forum . One key thing...
Introducing the Data Intelligence Platform for Communications
Join Databricks in a webinar overview of the Data Intelligence Platform for Communications The communications industry is undergoing one of the most significant...
Evolving Your SIEM Detection Rules: A Journey from Simple to Sophisticated
Cyber threats and the tools to combat them have become more sophisticated. SIEM is over 20 years old and has evolved significantly in...
Manufacturing Insights: Calculating Streaming Integrals on Low-Latency Sensor Data
Data engineers rely on math and statistics to coax insights out of complex, noisy data. Among the most important domains is calculus, which...
Announcing Ray Autoscaling support on Databricks and Apache Spark™
Ray is an open-source unified compute framework that simplifies scaling AI and Python workloads in a distributed environment. Since we introduced support for...