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.
Why big data analytics projects fail and how to fix them
Max Henrion
Max Henrion has 25 years of experience as a researcher, educator, software designer, consultant, and entrepreneur, specializing in the design and effective use of decision technologies. He is the Founder and CEO of Lumina Decision Systems. He has led teams to create decision-support tools in a wide variety of applications, including energy, environment, R&D management, healthcare, telecommunications, aerospace, security, and consumer choice. He is the lead designer of Lumina’s flagship product line, Analytica -— the software about which PC Week said “Everything that’s wrong with the common spreadsheet is fixed in Analytica”.
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