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Unified Analytics Platform

About technology

Given the highly iterative nature of AI development, companies need to cycle through the lifecycle of preparing data, training models, and production deployment quickly. Because data systems are not enabled for AI and AI frameworks such as TensorFlow, PyTorch, and SciKit-Learn don’t do data processing it’s very hard for enterprises to succeed in AI without an army of highly sophisticated engineers and data scientists. Databricks Unified Analytics Platform, powered by Apache Spark, lowers the barrier for enterprises to innovate with AI and accelerates their innovation. This managed Cloud service auto-scales Spark clusters and includes an enhanced version of Spark that is up to 50x faster. It adds data reliability to exploratory data stored in Cloud Data Lakes, making it much faster (weeks) and more reliable to build complex data pipelines at massive scale (prepare petabytes of historical data with real-time data) for AI. Databricks’ collaborative notebooks are tightly integrated with cloud-native Spark clusters and enable data scientists to productively execute their complete AI lifecycle - explore large datasets, AI applications data through simple SQL queries, advanced analytics in R and Python or build predictive models using ML/DL. It's the best-in-class collaborative platform that truly unifies data science and data engineering for fast iterations of data prep, model training and production deployment. Databricks’ customers also benefit from data security, compliance and reduced DevOps costs. All of this means organizations can finally apply AI across their data and drive disruptive innovations to the market.

Press and media coverage

Enterprise Innovation: Analytics for the 2019 enterprise https://www.enterpriseinnovation.net/article/analytics-2019-enterprise-177337658 UKAuthority:Building a culture of experimentation with data https://www.ukauthority.com/articles/building-a-culture-of-experimentation-with-data/ Computing: Optimised bidding and targeted advertising is a job for AI, says MediaGamma https://www.computing.co.uk/ctg/news/3065442/optimised-bidding-and-targeted-advertising-is-a-job-for-ai ZDnet: What Overstock.com learns about its customers from decades of data https://www.zdnet.com/article/what-overstock-com-learns-about-its-customers-from-decades-of-data/ EPM Magazine:Why a unified approach to big data is key https://www.epmmagazine.com/opinion/why-a-unified-approach-to-big-data-is-key/ ZDnet: Apache Spark creators set out to standardize distributed machine learning training, execution, and deployment https://www.zdnet.com/article/apache-spark-sets-out-to-standardize-distributed-machine-learning-training-execution-and-deployment/ Computing: How Nielsen is evolving into an AI-first business https://www.computing.co.uk/ctg/analysis/3065146/how-nielsen-is-evolving-into-an-ai-first-business TheRegister: Databricks pushes machine learning on easy mode: Rock star data scientist, meet sweaty engineer https://www.theregister.co.uk/2018/10/04/databricks_targets_messy_machine_learning_tools_technical_silos/ CIO: How AI is revolutionizing manufacturing https://www.cio.com/article/3302797/artificial-intelligence/how-ai-is-revolutionizing-manufacturing.html Datanami: Five Ways to Unshakle Data Science From IT Now https://www.datanami.com/2018/08/27/five-ways-to-unshackle-data-science-from-it-now/ JaxEnter: For AI success, developers should collaborate more efficiently with data scientists & engineers https://jaxenter.com/ai-success-interview-databricks-148117.html