The purpose of Big Data is to supply companies with actionable information on any variety of aspects. But this is proving to be far more difficult than it looks. Studies have shown that more than half of Big Data projects are left uncompleted, with 58% of them citing inaccurate scope as a cause. This hints at a widespread shortcoming of Big Data project management.
In fact, two of the most often reported reasons for project failures are a lack of expertise in data analysis, both from a correlative and contextual standpoint. Reports show that data processing, management and analysis are all difficult in any phase of the project, with IT teams citing each of those reasons more than 40% of the time.
However, failures in Big Data projects may not solely lie on faulty project management. In a recent survey, a staggering 80% of Big Data’s biggest challenges are from a lack of appropriate talent. The field’s relative infancy is making it hard for Big Data enterprises to find the necessary staff to see projects to fruition. The result is underutilized data and missed project goals.
IT teams are quickly recognizing a chasm between executives and frontline staffers whose job it is to apply the findings from Big Data. In the end, Big Data may not be the anticipated cure-all for 21st century business management. It is only as good as good as the system that runs it.