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Agile Data Science: Examples from experience!
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Jonathan Rapisarda shares a practical, Agile approach to using inexpensive cloud technology to create actionable data insights.

3/23/2017
When: Usually the 4th Thu ea month
5:30 PM - 7:30 PM
Where: RevGen Partners
6300 S Syracuse Way, Suite 120
Centennial, Colorado  80111
United States
Presenter: Jonathan Rapisarda
Contact: Lynn Winterboer
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Data science as it applies to artificial problem solving and enhanced decision is something that NASA and other large organizations have been doing since the 1960’s. In 2012, there was a bit a of cultural revelation as the world collectively began to realize that computing power had advanced to the point where models could be trained inexpensively and provide incredible amounts of value to businesses as well as opportunities for cost savings and market share expansion. 

Jonathan's approach is holistic and can be applied to everything from day to day life (i.e., personal investing strategies) or to enterprise concerns such as predetermination of equipment failure in large scale industries. The approach is Agile in nature as project teams can be formed rapidly according to skill-sets and teams can be very self-directing and produce realized results which make it to production quickly without impacting existing systems. MVP (minimum viable product) solutions can be deployed within weeks and then enhanced as users engage and provide feedback based on the quality of the decision support provided. Sprints form themselves and it becomes very easy to get continued executive buy-in for the progress the teams can make.  

According to Gartner, the industry will save in costs or generate in revenue over $33 trillion in the next 10 years. In truth, this is a conservative estimate and there is money to be had by all because no single player will be able to emerge as the primary driving force behind the innovation that can be mustered through individual teams with solid knowledge of their organization and the industry in which they operate. 

Jonathan’s approach is customized to the problem at hand. In this session, he provides two practical examples of how to apply this approach.

About the Speaker:

Jonathan Rapisarda views data science as an art and not a hard and fast series of algorithms, as those have been in place for decades. He has been blessed in getting the opportunity to learn originally from some of the best in the world during his tenure at IHS-Markit (back when it was IHS) where the VP of Data created a “cult of data excellence” mentality that infused Jonathan at an impressionable point in his career with an understanding of the intricacies of what data can do and how powerful it can be when viewed correctly. 

Jonathan is now Chief Technical Architect of a public benefits company that uses data to provide the world with advanced technologies using data as the lifeblood to improve the quality of life while maintaining a profit-motive.

Jonathan holds an MBA, and is more focused on proving first and then talking about his ideas after they have shown value, instead of before they work. 


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