Why So Many Data Science Projects Fail to Deliver:

Many companies are unable to consistently gain business value from their investments in big data, artificial intelligence, and machine learning. A study of the data science functions and initiatives in three of India's largest private-sector banks identified five obstacles to successful data sc...

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Bibliographic Details
Main Authors: Joshi, Mayur (Author), Austin, Robert (Author), Su, Ning (Author), Sundaram, Anand (Author)
Corporate Authors: O'Reilly for Higher Education (Firm) (Contributor), Safari, an O'Reilly Media Company (Contributor)
Format: Electronic eBook
Language:English
Published: [Erscheinungsort nicht ermittelbar] MIT Sloan Management Review 2021
Edition:1st edition.
Links:https://learning.oreilly.com/library/view/-/53863MIT62317/?ar
Summary:Many companies are unable to consistently gain business value from their investments in big data, artificial intelligence, and machine learning. A study of the data science functions and initiatives in three of India's largest private-sector banks identified five obstacles to successful data science projects and suggests remedies that can help companies obtain more benefit from their data science investments.
Item Description:Online resource; Title from title page (viewed March 2, 2021)
Physical Description:1 Online-Ressource (7 Seiten)