DataRPM Announces Its Version 8.0 Platform

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datarpm_logoStrata + Hadoop World News

DataRPM, backed by InterWest Partners and Cloudera Co-Founder Dr. Amr Awadallah, announced Version 8.0 of its leading smart machine insights software, aiming to make the next leap in machine-led Data Intelligence.

With the announcement at the Strata Conference in San Jose, DataRPM establishes leadership in the most advanced technology designed to bring effective analytics to the world of Hadoop Big Data. The product, Smart Machine Insights, uses machine learning to automatically model the data, perform advanced statistical analyses, and present key insights to users in an easy to use visual format.

Every year billions of dollars are invested into data analysis, yet struggles continue due to a shortage of expertise. According to a report from IDC, only 0.5% of data is ever analyzed, and McKinsey reported that by 2018 the United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise.

This is not a human scale issue, it’s a machine scale issue,” says CEO of DataRPM Sundeep Sanghavi. “As Smart Machines dominate the disruption in the next decade, the only way to provide any insights in any reasonable time frame is through machines. Current data discovery tools presume that the enterprise knows where to look and what to specifically ask and have enough resources and skills to address it. As we learned with one of our smart enterprise customer, Cisco, this assumption is simply flawed, hence we are advancing beyond data discovery to insights discovery using smart machines, which will completely reshape how analytics is performed on Hadoop infrastructure.”

DataRPM Version 8.0 runs natively within Hadoop. Once connected on the federated data, the algorithms automatically discovers entities and relationships in the data and conducts statistical analyses and hypothesis tests. This includes machine learning algorithms such as time-series analysis, forecasting, prediction, root cause analysis, anomaly detection, recommendations and others.


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