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5 Key Reasons Why Analytics Projects Fail

With the news full of so many successes in the fields of Analytics, machine learning and artificial intelligence, it is easy to lose sight of the high failure rate of analytics projects.  McKinsey just came out with a report that only 8% of big companies (revenue > $ 1 billion) have successfully scaled and integrated analytics throughout the organization. In some ways, the very notable successes of analytics and data science contribute to the high failure rate, as ill-prepared organizations flock to implement projects.  There are various reasons for failure, and all are instructive.



This post first appeared on Elder Research Data Science & Machine Learning Blog, please read the originial post: here

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5 Key Reasons Why Analytics Projects Fail

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