How can modern enterprises unlock the potential of AI to change their business? Today’s businesses and enterprises are increasingly focused on big data that can help drive innovation and transformation through the potential of artificial intelligence. According to a survey and research report commissioned with IDG’s CIO, nearly 90 percent of enterprises are investing in data and AI technology. Download the new report, “Unified Analytics for Dummies,” that explores the steps to AI success in today’s market.
Databricks and RStudio Introduce New Version of MLflow with R Integration
October 14, 2018 by
Databricks, a leader in unified analytics and founded by the original creators of Apache Spark™, and RStudio, today announced a new release of MLflow, an open source multi-cloud framework for the machine learning lifecycle, now with R integration. RStudio has partnered with Databricks to develop an R API for MLflow v0.7.0.
Databricks Partners with RStudio To Increase Productivity of Data Science Teams
June 29, 2018 by
Databricks, a leader in unified analytics and founded by the original creators of Apache Spark™, announced a partnership with RStudio, providers of a free and open-source integrated development environment for R, to increase the productivity of data science teams. The partnership will allow the two companies to seamlessly integrate Databricks’ Unified Analytics Platform with the RStudio Server, simplifying R programming on big data.
Databricks Conquers AI Dilemma with Unified Analytics
June 10, 2018 by
Databricks, a leader in unified analytics and founded by the original creators of Apache Spark™, addresses this AI dilemma with the Unified Analytics Platform. The company launched new capabilities to lower the barrier for enterprises to innovate with AI. These new capabilities unify data and AI teams and technologies: MLflow for developing an end-to-end machine learning workflow, Databricks Runtime for ML to simplify distributed machine learning; and Databricks Delta for data reliability and performance at scale.
Apache Spark 2.0: A Deep Dive Into Structured Streaming
May 28, 2018 by
In this talk, Tathagata Das takes a deep dive into the concepts and the API and show how this simplifies building complex “Continuous Applications”. Tathagata is an Apache Spark Committer and a member of the PMC. He’s the lead developer behind Spark Streaming, and is currently employed at Databricks.
The Data Scientist’s Guide to Apache Spark
December 27, 2017 by
Looking to dive deeper into the more cutting edge machine learning use cases in Apache Spark? To successfully use Spark’s advanced analytics capabilities including large scale machine learning and graph analysis, check out The Data Scientist’s Guide to Apache Spark, from our friends over at Databricks.
Databricks Launches Delta To Combine the Best of Data Lakes, Data Warehouses and Streaming Systems
October 26, 2017 by
Databricks, provider of the leading Unified Analytics Platform and founded by the team who created Apache Spark™, announced Databricks Delta, the first unified data management system that provides the scale and cost-efficiency of a data lake, the query performance of a data warehouse, and the low latency of a streaming ingest system. Databricks Delta, a […]
Databricks Secures $140 Million to Accelerate Analytics and Artificial Intelligence in the Enterprise
August 23, 2017 by
Databricks, provider of the leading Unified Analytics Platform and founded by the team who created Apache Spark™, announced it has secured $140 million in a Series D funding round led by Andreessen Horowitz. New Enterprise Associates and Battery Ventures also participated.
Databricks Simplifies and Scales Deep Learning with New Apache Spark Library
June 7, 2017 by
Databricks, the company founded by the creators of the popular Apache Spark project, announced Deep Learning Pipelines, a new library to integrate and scale out deep learning in Apache Spark.
Databricks Launches New Edition of Its Spark-Based Cloud Platform for Data Engineers
May 22, 2017 by
Databricks, the company founded by the creators of the popular Apache Spark project and providers of the leading Spark-based cloud platform for data science, announced an edition of its cloud platform optimized specifically for data engineering workloads called Databricks for Data Engineering.
