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Using a developer friendly notebook and a wide range of open source data science tools that integrate directly with the MapR Platform, the MapR Data Science Refinery is easy to deploy using a secure, persistent, and extensible container that can be distributed to many data science teams across multi-tenant environments.
“There are many limitations with current data science self-service solutions that prevent them from offering comprehensive machine learning and processing,” said Anoop Dawar, vice president, product marketing and management, MapR. “MapR provides a scalable integrated offering with native platform access and superior out-of-the-box security. Our goal is to help speed accuracy of insights and empower data scientists to be the agent of change in an economy where data is the new commodity to be refined.”
The MapR Data Science Refinery includes a comprehensive data science notebook that supports a broad range of open source tooling, compute and query engines, and libraries for exploration, collaboration and visualisation. Breaking down siloed roles in organisations undergoing digital transformation, the MapR Data Science Refinery enables data scientists to work more effectively with developers as part of a data-focused DataOps team to deploy highly effective operational applications.
Additionally, the MapR Platform provides a global namespace and superior replication capability making it the perfect platform for model and notebook repository sharing and mirroring. The MapR Platform enables real-time machine learning pipelines to help incorporate artificial intelligence into business workflows at scale.
As an extension of the MapR Data Science Refinery, MapR will work closely with companies, such as H2O.ai, DataScience.com and C3IoT, to provide additional machine learning and other analytical tools to improve the data scientist experience.
"H2O democratises AI for enterprises and businesses looking to monetise investments in their data infrastructure.” says Sri Ambati, CEO at H2O.ai, “With MapR and H2O, data scientists can now use lightning fast machine learning on all of their data. They can achieve accuracy faster to drive real-time predictions. The joint solution also allows data scientists to operationalise sophisticated and simple models from training to production on the same interactive platform.”
"We're excited to partner with MapR to bring our enterprise data science platform to our joint customers," said William Merchan, chief strategy officer, DataScience.com. "By integrating directly with the MapR Data Science Refinery, we can provide a truly compelling offering that enables data science jobs to be deployed directly on the MapR cluster for fast data access and better resource utilisation. Our collaboration with MapR greatly enhances the ability of our customers to analyse and deploy models for mission-critical production applications at scale.”
