Data Virtualization and Big Data: A 'Virtual Case Study' Enterprise Apps Today Data virtualization and Big Data are a match made in analytics heaven, according to Wayne Kernochan of Infostructure Associates.
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 with over half of Big Data projects left uncompleted.
Two of the most often reported reasons for project failures are a lack of expertise in data analysis. 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 to find the necessary staff to see projects through, resulting in underutilized data and missed project goals.
IT teams are quickly recognizing a chasm between executives and frontline staffers whose job it is to apply findings from Big Data. In the end,it 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.
Few companies manage information better than Google. If there were an annual award for corporate information management (IM), I’m sure that Google would have won it–or had been in the top three–over the past decade.
Big Data's Big Opportunity in the Bleak Economy of 2013 Forbes “Big Data could be huge this year,” Barry Trailer of CSO Insights told SAP's Bonnie D. Graham during last week's 2013 Predictions episode of her weekly Coffee Break with Game-Changers.
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