Actualizing Business Value from Machine Learning and Enterprise Data Science

Arjuna Swaminathan

Data Science & AI Solutions Executive at IBM Corporation

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While enterprises continue to invest more, driving the Big Data Analytics market to grow at an expected 12% CAGR through 2027, it is estimated that 85% of big-data projects fail. Furthermore, a recent survey of US executives suggesting that 63% of them do not believe that their companies are analytics driven, points to opportunities to derive greater value from investments in Data Science. Starting data science initiatives with broad consensus on business challenges to be addressed, and clear articulation of success criteria contributes to an enterprise’s ability to make appropriate investments in the right skills, tools, platform, and processes. Organizations also need an effective approach to operationalize data science to derive the anticipated business benefits. In this webinar, you will learn about recent trends impacting Data Science, common challenges, and best practices to operationalize Enterprise Data Science.

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