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As a digital society built around data and devices, we have reached a pivotal juncture where data and Artificial Intelligence must be accessible to everyone. Riding this trend, many homes now contain smart devices such as the Amazon Echo or Google Home. Yet these devices only offer limited computational power and AI capabilities. To remedy...

In recent years, machine learning has become ubiquitous in industry and production environments. Both academic and industry institutions had previously focused on training and producing models, but the focus has shifted to productionizing the trained models. Now we hear more and more machine learning practitioners really trying to find the right model deployment options. In...

It’s hard to believe that we are already three weeks into 2018. If you’re still struggling to get valuable insights from your data, now is the perfect time to try something new! We recently announced Azure Databricks, a fast, easy and collaborative Apache® Spark™ based analytics platform optimized for Azure. With Azure Databricks, you can help your...

Today we released our Databricks Unified Analytics Platform video. This short video illustrates to analytics leaders how Databricks can unify their analytics efforts onto one platform. This unification makes analytics teams more efficient and enables them to tackle tougher analytics problems. Many organizations are moving to Spark for the awesome big data processing power it...

High-profile cybersecurity breaches dominated headlines in 2017. In the first half of the year, over 1.9B records were stolen. That’s more than 7,000 records breached every minute. And the fallout from a single event can be staggering. Customer attrition, negative PR and regulatory fines amount to millions in financial losses. In fact, according to recent...

Big data workloads require access to disk space for a variety of operations, generally when intermediate results will not fit in memory. When the required disk space is not available, the jobs fail. To avoid job failures, data engineers and scientists typically waste time trying to estimate the necessary amount of disk via trial and...

This is a joint blog post from Matei Zaharia, Chief Technologist at Databricks and Peter Carlin, Distinguished Engineer at Microsoft. Today at Microsoft Connect(); we introduced Azure Databricks, an exciting new service in preview that brings together the best of the Apache Spark analytics platform and Azure cloud. As a close partnership between Databricks and...

99% of organizations still struggle to get valuable analytics from their Big Data and achieve the full potential of AI. Today I’m excited to announce a new partnership with Microsoft that represents a major leap forward in achieving Databricks’ mission of making Big Data and AI easy: Databricks will now be offered by Microsoft as...

Introduction As part of Unified Analytics Platform, Databricks Workspace along with Databricks File System (DBFS) are critical components that facilitate collaboration among data scientists and data engineers: Databricks Workspace manages users’ notebooks, whereas DBFS manages files; both have REST API endpoints to manage notebooks and files respectively. While the REST APIs are principally designed for...

Databricks, the Unified Analytics Platform, has always been a cloud-first platform. We believe in the scalability and elasticity of the cloud so that customers can easily run their large production workloads and pay for exactly what they use. Hence, we have been charging our customers at per-second level granularity. Until last month, billing on AWS...