CIO Survey: Top 3 Challenges Adopting AI and How to Overcome Them

Posted Leave a commentPosted in AI, Announcements, CIO, Company Blog, data, Events, ML, Product, Survey, Unified analytics

  We recently hosted the webinar — CIO Survey: Enterprise Challenges to AI and How to Overcome Them — featuring Jen Garofalo, Research Director at IDG, the parent company to, and Pat McDonough, VP of Customer Success at Databricks. This webinar covered key findings from a recent survey of 200 executives on the […]

Introducing Databricks Runtime 5.0 for Machine Learning

Posted Leave a commentPosted in Announcements, Company Blog, Databricks Runtime 5.0 ML, Deep Learning, Ecosystem, Engineering Blog, Machine Learning, Platform

Six months ago we introduced the Databricks Runtime for Machine Learning with the goal of making machine learning performant and easy on the Databricks Unified Analytics Platform. The Databricks Runtime for ML comes pre-packaged with many ML frameworks and enables distributed training and inference. Today we are excited to release the second iteration including Conda […]

Are you ready to scale your Data and AI initiatives? How will you scale your security?

Posted Leave a commentPosted in Company Blog, Enterprise Security, Security

This is Blog #3 in a series of blog posts about Databricks security. My colleagues David Cook (our CISO) and David Meyer (SVP products) laid out Databricks’ approach to Security in blog #1  & blog #2. With this blog, I will be talking about deploying and operating  Databricks at scale while minimizing human error. Democratize […]

Announcing Databricks Runtime 5.0 – The Databricks Blog

Posted Leave a commentPosted in Announcements, Apache Spark, Company Blog, Product

We’re excited to announce the general availability of Databricks Runtime 5.0. Included in this release is Spark 2.4. This release offers substantial performance increases within key areas of the platform. Benchmarking workloads have shown a 16% improvement in total execution time and Databricks Delta benefits from substantial improvements to metadata caching, improving query latency by […]

MongoDB Atlas: Connector for Apache Spark now Officially Certified for Azure Databricks

Posted Leave a commentPosted in Announcements, Azure, Company Blog, MongoDB, Partners

This is a guest blog from our partners at MongoDBBryan Reinero and Dana Groce We are happy to announce that the MongoDB Connector for Apache Spark is now officially certified for Azure Databricks. MongoDB Atlas users can integrate Spark and MongoDB in the cloud for advanced analytics and machine learning workloads by using the MongoDB […]

Open Sourcing Databricks Integration Tools at Edmunds

Posted Leave a commentPosted in Apache Spark, Company Blog, Customers, Engineering Blog, Platform

This is a guest post from Shaun Elliott, Data Engineering Tech Lead and Sam Shuster, Staff Engineer at Edmunds. What is Databricks and How is it Useful for Edmunds? Databricks is a cloud-based, fully managed, big data and analytics processing platform that leverages Apache SparkTM and the JVM. The big selling point of the Databricks Unified […]

The three biggest security challenges facing AI and data initiatives

Posted Leave a commentPosted in Company Blog, Databricks Platform, Enterprise Security, platform security, Security, Unified Analytics Platform

In today’s business climate, the ability to anticipate and meet customer needs is central to success. Forward looking business leaders are looking to unleash the power of Artificial Intelligence (AI) to drive innovation, but this requires bringing together diverse teams and large volumes of data. With attackers getting more sophisticated, securing these complex data workflows […]