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Many analyst professionals might think it’s some kind of “data nirvana” to achieve self-service data science. It’s easy to see why. You have a difficult time hiring the right talent. Based on the Annual CDO Survey from Gartner, 59% of Chief Data Officers say they feel too far behind on attracting and hiring analyst talent. Once you do hire talent, organizations report they can only analyze 12% of their data accurately.
The great news is that it’s possible to achieve this “data nirvana” and offer self-service data science. Dr. Mike Kim, Co-Founder and CTO of Outlier, will present in this session the following:
What are some of the current challenges to consider before migrating to self-service?
How automating collection and analysis phases of data science can help to achieve self-service
Examples of organizations who have adopted a self-service data science philosophy
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