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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Beteiligte Personen: Joshi, Mayur (VerfasserIn), Austin, Robert (VerfasserIn), Su, Ning (VerfasserIn), Sundaram, Anand (VerfasserIn)
Körperschaften: O'Reilly for Higher Education (Firm) (MitwirkendeR), Safari, an O'Reilly Media Company (MitwirkendeR)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: [Erscheinungsort nicht ermittelbar] MIT Sloan Management Review 2021
Ausgabe:1st edition.
Links:https://learning.oreilly.com/library/view/-/53863MIT62317/?ar
Zusammenfassung: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.
Beschreibung:Online resource; Title from title page (viewed March 2, 2021)
Umfang:1 Online-Ressource (7 Seiten)