Why big data analytics projects fail and how to fix them

If you are like most practitioners of analytics, you went into the field because you are good with numbers, and you want to help people improve the quality of decisions on important issues. But many of us spend too much time struggling to organize poorly structured data and debugging complex spreadsheets or code and too little time engaging directly with our clients to help them clarify their objectives and decisions, brainstorm better decision options, and explore, visualize and understand the results. Without this kind of interaction, the analysis may fail to address the issues they really care about. Even if it does, clients may not develop the confidence to rely on the insights, and you end up frustrated that your hard work fails to be properly appreciated.