01. Chris Devaney, DataRobot, Visits theCUBE. (00:14)
02. Automated Machine Learning Platform. (00:34)
03. Scaling Data Science. (01:45)
04. DataRobot University. (05:42)
05. Baseball Player Selection Using DataRobot. (07:01)
06. Getting Started with DataRobot. (08:43)
07. Attracting the Best Talent. (10:30)
08. The Vision for DataRobot. (11:28)
09. Interest in Predictive Analytics. (14:30)
10. Growth of DataRobot. (15:33)
https://siliconangle.com/2016/03/29/data-science-no-coding-required-datarobots-automated-platform-has-guard-rails-for-non-data-scientists-bigdatasv/
#theCUBE #DataRobot #SiliconANGLE #BigDataSV
--- ---
Data science, no coding required: DataRobot’s automated platform has ‘guard-rails’ for non-data scientists | #BigDataSV
by Betsy Amy-Vogt | Mar 29, 2016
The team from DataRobot, Inc. believes that every company in the world can benefit from predictive analytics, but there just aren’t enough data scientists out there to cover the demand. So its automated data analysis platform enables non-data scientists to create accurate, fast models with no coding knowledge.
Chris Devaney, VP of operations at DataRobot, Inc. joined John Furrier (@furrier) and Jeff Frick (@jefffrick), cohosts of theCUBE, from the SiliconANGLE Media team, at the Fairmont San Jose in San Jose, California, where BigDataSV 2016 celebrates #BigDataWeek, including news and events from the #StrataHadoop conference.
Automation increases productivity
As well as letting business analysts do data science and protecting them from making bad decisions with built-in “guard rails,” DataRobot’s advanced machine learning platform is a tool for data scientists, upping productivity levels in time to create a model from weeks and months to just days and hours.
This decrease in work time required effectively solves the issue of how to scale data science as data scientists are able to accomplish more in less time.
Not just fast, but accurate
The goal is not just to find a good model to solve a problem but to find the best model to solve a specific problem. Devaney explained how DataRobot’s platform was developed by a team of the world’s top data scientists to be able to quickly and accurately determine the top prediction model for each use-case.
Predictive analytics for everyone
“We leverage all infrastructure,” said Devaney, emphasizing DataRobot’s goal to make data science and predictive analytics available to all companies and describing how DataRobot interacts with everything from bare metal Linux to Cloudera.
Playing the World Series with DataRobot
Citing a fun use-case scenario, Devaney talked about how the New York Mets implemented DataRobot and used it for its player selections for the 2015 season. The team advanced to the World Series that season for the first time since 2000 and came close to winning, eventually coming in second.
“We like to think it was thanks to DataRobot,” said Devaney.
@theCUBE
#BigDataSV #StrataHadoop @DataRobot @SiliconANGLE theCUBE #theCUBE
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Chris Devaney, DataRobot | Big Data Silicon Valley 2016
01. Chris Devaney, DataRobot, Visits theCUBE. (00:14)
02. Automated Machine Learning Platform. (00:34)
03. Scaling Data Science. (01:45)
04. DataRobot University. (05:42)
05. Baseball Player Selection Using DataRobot. (07:01)
06. Getting Started with DataRobot. (08:43)
07. Attracting the Best Talent. (10:30)
08. The Vision for DataRobot. (11:28)
09. Interest in Predictive Analytics. (14:30)
10. Growth of DataRobot. (15:33)
https://siliconangle.com/2016/03/29/data-science-no-coding-required-datarobots-automated-platform-has-guard-rails-for-non-data-scientists-bigdatasv/
#theCUBE #DataRobot #SiliconANGLE #BigDataSV
--- ---
Data science, no coding required: DataRobot’s automated platform has ‘guard-rails’ for non-data scientists | #BigDataSV
by Betsy Amy-Vogt | Mar 29, 2016
The team from DataRobot, Inc. believes that every company in the world can benefit from predictive analytics, but there just aren’t enough data scientists out there to cover the demand. So its automated data analysis platform enables non-data scientists to create accurate, fast models with no coding knowledge.
Chris Devaney, VP of operations at DataRobot, Inc. joined John Furrier (@furrier) and Jeff Frick (@jefffrick), cohosts of theCUBE, from the SiliconANGLE Media team, at the Fairmont San Jose in San Jose, California, where BigDataSV 2016 celebrates #BigDataWeek, including news and events from the #StrataHadoop conference.
Automation increases productivity
As well as letting business analysts do data science and protecting them from making bad decisions with built-in “guard rails,” DataRobot’s advanced machine learning platform is a tool for data scientists, upping productivity levels in time to create a model from weeks and months to just days and hours.
This decrease in work time required effectively solves the issue of how to scale data science as data scientists are able to accomplish more in less time.
Not just fast, but accurate
The goal is not just to find a good model to solve a problem but to find the best model to solve a specific problem. Devaney explained how DataRobot’s platform was developed by a team of the world’s top data scientists to be able to quickly and accurately determine the top prediction model for each use-case.
Predictive analytics for everyone
“We leverage all infrastructure,” said Devaney, emphasizing DataRobot’s goal to make data science and predictive analytics available to all companies and describing how DataRobot interacts with everything from bare metal Linux to Cloudera.
Playing the World Series with DataRobot
Citing a fun use-case scenario, Devaney talked about how the New York Mets implemented DataRobot and used it for its player selections for the 2015 season. The team advanced to the World Series that season for the first time since 2000 and came close to winning, eventually coming in second.
“We like to think it was thanks to DataRobot,” said Devaney.
@theCUBE
#BigDataSV #StrataHadoop @DataRobot @SiliconANGLE theCUBE #theCUBE
