There are seven key factors that can mean the difference between an analytics project succeeding, or adding to the high statistic of big data project failures; a failure rate Gartner puts at 85%.
This is according to Karl Dinkelmann, director of data enablement, business intelligence (BI) and analytics at AccTech Systems, who told delegates at ITWeb Business Intelligence and Analytics Summit 2019 this week that all indications point to the fact that any company embarking on an analytics project has an 8.5 out of 10 chance of failing. “Analytics projects fail not because the solution doesn’t work, but because the business fails to realise value from its investment, or the technology is not used at all. The cost of this failure is enormous,” he said.
Author: Marilyn de Villiers
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