Use Databricks Pools to Speed up your Data Pipelines and Scale Clusters Quickly
Data Engineering teams deploy short, automated jobs on Databricks. They expect their clusters to start quickly, execute the job, and terminate. Data Analytics teams run large auto-scaling, interactive clusters on Databricks. They expect these clusters to adapt to increased load and scale up quickly in order to minimize query latency. Databricks is pleased to announce...
New Microsoft Azure Data Warehouse Service and Azure Databricks Combine Analytics, BI, and Data Science
In the last two years since it first became available, thousands of companies have adopted Azure Databricks, making it one of the fastest growing data and AI services on Microsoft Azure. Customers now process over 2 exabytes per month with millions of server-hours spinning up every day. All of this is driven by organizations like...
Do you DIY your AI? You are probably failing on security.
This is Blog #2 in a series of blog posts about Databricks security. My colleague David Cook (our CISO) laid out Databricks' approach to Security in blog #1. With this blog, I will be talking in detail about our platform. DIY Platforms: A Lack of Cohesion in Security Many companies today operate on homegrown DIY big...