As promised, here is the second half of Jamie Menashi’s viewpoints on why BI/analytics projects either do not meet expectations, or fail outright. The first blog on this subject, along with bio information about Jamie, is here. In this era of big data, as organizations of all stripes try to either (a) stretch their existing BI/analytics solution, or (b) jump to a more modern version, they inevitably run into difficulties as they scale big data’s walls. As you will learn from Jamie, the reasons for failure or dissatisfaction usually have more to do with culture, process, and decision-maker oversights, more so than the underlying technology.
Reason 2
My IT department will do it and learn as they go. High value BI/analytics projects are part technology, part business and part art. We want to use information to guide behavior and decisions and we need the right team to make…
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