Creating a Data Culture with Rohan Kumar and Santosh Jamadagni

About Show #834

Does your organization have a data culture? Richard talks with Microsoft CVP Rohan Kumar, and Mars VP Santosh Jamadagni about building organizations focused on data rather than opinion to drive the company forward. Rohan talks about getting data out of silos and into the hands of folks that can act on the information to make better business decisions. Santosh discusses how Mars has empowered workers throughout the Mars organization with real-time information. The conversation digs into the need to apply security rules to data as it enters the organization so that it is immediately available to the right people at the right time. Data availability is the key to a data culture!


Recorded May 4, 2022


Rohan Kumar is the corporate vice president of Azure Data at Microsoft. He leads the technical product strategy, vision, design and development of integrated solutions for database, analytics and governance platforms within Azure Data Services. His team focuses on building systems to help customers and partners realize the maximum value of their data - to make informed business decisions, simplify their operations, govern their data - and achieve positive outcomes. Rohan joined Microsoft in July 1998 as a software development engineer in the Windows team. Rohan graduated with a Bachelor of Technology degree in Computer Science and Engineering from Indian Institute of Technology, BHU and a Master of Science degree in Computer Science from University of Massachusetts at Amherst.

Santosh Jamadagni joined Mars Inc. in March 2018 and is currently responsible for managing the global Data and Integration Platforms. Over the last two years, he has focused on building platform services that enable product teams to deliver value at 100x, conform with Mars security and privacy standards, and optimize the total cost to serve. He has championed establishing data driven culture, modernizing the data foundation, implementing data engineering and virtualization technologies, formulating a data engine for effective governance and asset reuse, and streamlining production deployment with ML engineering / feature store.

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