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Make Data Work
Oct 15–17, 2014 • New York, NY
Rohit Jain

Rohit Jain
Chief Technology Officer, Esgyn

Rohit Jain is the CTO at Esgyn for Trafodion, a transactional SQL-on-HBase RDBMS. Rohit worked for Hewlett-Packard for 28 years on applications and databases, undertaking such roles as solutions architect, consultant, software engineer, architect, development and QA manager, product manager, and chief technologist in fields including online transaction processing, operational data stores, data marts, enterprise data warehouses, business intelligence, and advanced analytics on distributed massively parallel systems.


9:00am–5:00pm Wednesday, 10/15/2014
Data-Driven Business Day
Location: 1 E20/1 E21
Alistair Croll (Solve For Interesting), Farrah Bostic (The Difference Engine), Edd Wilder-James (Google), Jennifer Zeszut (Beckon), Brian Dalessandro (Capital One), Jana Eggers (Nara Logics), Joe Caserta (Caserta Concepts), Joy Beatty (Seilevel), kim rees (Periscopic), Peter Ferns (Goldman Sachs & Co), Brigitte Piniewski (nonaffiliated ), Nellwyn Thomas (Etsy), Michael Rosenbaum (Pegged Software), Merici Vinton (OI Engine @ IDEO ), Mary Ann Wayer (Premier Inc), Rohit Jain (Esgyn), Amy Gaskins (Panopticon), Jen van der Meer (Reason Street), Mark Doms (United States Department of Commerce), Halle Tecco (Rock Health)
Average rating: ***..
(3.33, 12 ratings)
All-Day: For business strategists, marketers, product managers, and entrepreneurs, Data-Driven Business looks at how to use data to make better business decisions faster. Packed with case studies, panels, and eye-opening presentations, this fast-paced day focuses on how to solve today's thorniest business problems with Big Data. It's the missing MBA for a data-driven, always-on business world. Read more.
2:10pm–2:20pm Wednesday, 10/15/2014
Data-Driven Business Day
Location: E 20/ E 21
Rohit Jain (Esgyn)
Average rating: **...
(2.33, 3 ratings)
We had a big, and growing, global platform for storing and sharing people's most precious memories. But we had a problem. Size and scale meant traditional RDBMS wouldn't work. It was slow, error prone, and gave users a worse experience the more successful we became... Read more.