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We are excited to announce General Availability (GA) of the Microsoft Power BI connector for Databricks for Power BI Service and Power BI Desktop 2.85.681.0. Following the public preview, we have already seen strong customer adoption, so we are pleased to extend these capabilities to our entire customer base. The native Power BI connector for...

For years Hadoop was the default technology for big data analytics. But over time, it has fallen behind as new technologies have been introduced to provide better analytics solutions. Many organizations are looking at their Hadoop costs and trying to justify migrating to a modern cloud-based analytics platform. Databricks just released the whitepaper, “The Hidden...

Today, we are proud to announce the availability of Databricks on Google Cloud. This jointly developed service provides a simple, open lakehouse platform for data engineering, data science, analytics, and machine learning. It brings together the Databricks capabilities customers love with the data analytics solutions and global scale available from Google Cloud. Open data platform...

Data analysts, data scientists, and artificial intelligence experts are often frustrated with the fundamental lack of high-quality, reliable and up-to-date data available for their work. Some of these frustrations are due to known drawbacks of the two-tier data architecture we see prevalent in the vast majority of Fortune 500 companies today. The open lakehouse architecture and underlying technology can dramatically improve the productivity of data teams and thus the efficiency of the businesses employing them.

In this blog, you will learn a series of steps you can take to harden your Databricks deployment from a network security standpoint, reducing the risk of Data exfiltration happening in your organization. Data Exfiltration is every company's worst nightmare, and in some cases, even the largest companies never recover from it. It’s one of...

Databricks was founded under the vision of using data to solve the world’s toughest problems. We started by building upon our open source roots in Apache Spark™ and creating a thriving collection of projects, including Delta Lake, MLflow, Koalas and more. We’ve now built a company with over 1,500 employees helping thousands of data teams...

We recently held a virtual event, featuring CEO Ali Ghodsi, that showcased the vision of Lakehouse architecture and how Databricks helps customers make it a reality. Lakehouse is a data platform architecture that implements similar data structures and data management features to those in a data warehouse directly on the low-cost, flexible storage used for...

Last week, Gartner published the Magic Quadrant (MQ) for Cloud Database Management Systems, where Databricks was recognized as a Visionary in the market.1 This was the first time Databricks was included in a database-related Gartner Magic Quadrant. We believe this is due in large part to our investment in Delta Lake and its ability to...

“Everything should be as simple as it can be, but not simpler” - Albert Einstein Generally, a simple data architecture is preferable to a complex one. Code complexity increases points of failure, requires more compute to run jobs, adds latency, and increases the need for support. As a result, data pipeline performance degrades over time,...

Today, at the Data + AI Summit Europe 2020, we shared some exciting updates on the next generation Data Science Workspace - a collaborative environment for modern data teams - originally unveiled at Spark + AI Summit 2020. The power of data and artificial intelligence is already disrupting many industries, yet we've only scratched the...