Big-Data/Analytics Projects Failure: A Literature Review

Description

Nowadays, no one doubt that big data and analytics are fundamental tools for successfully running an enterprise. However, big data/analytics projects do not seem to be all sunshine and rainbows, and this is documented by many sources providing startling figures of failed projects. Motivated by such figures, we conducted a (grey and scientific) literature review aimed to answer: RQ1) Which are the documented cases of failed BD/A projects, and which are the root causes of their failures? RQ2) What is assumed useful to reduce the chance of failure of BD/A projects? We collected and examined 188 sources. The survey resulted first in a list of hints for helping avoid the failure of the BD/A projects (RQ2), and in a list of 21 cases of failed BD/A projects documented in the literature (RQ1). The analysis of those failures resulted in confirming the hints of RQ2 and prompting other relevant ones. The result of this study will be useful not only to people developing a BDA project but also to researchers investigating the challenges proposed by a BDA project to the traditional methods of software engineering.

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