The Ten Most Common Data Mining Business Mistakes

White Paper


The results of data science and machine learning applications can have big payoffs, but the implementation of data mining techniques can also present substantial challenges. Many companies fail to reap the benefits because they make crucial mistakes in planning and deployment.

This paper discusses the ten business mistakes that frequently cause data science projects to fall short of expectations.

Awareness of these common mistakes will better equip organizational leaders to plan and guide analytics engagements to successful conclusions.

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