Few top-level executives understand the changes necessary in data-gathering and decision-making processes well enough to make big-data migrations a real priority.
12 Top Big Data Analytics Players
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Being able to collect more data on customers and shovel it into an analytic engine is only half the capability most companies need to develop, however, according to Larry Kanter, a forensic accountant and president of Kanter Financial Forensics in Dallas.
Good analysis and decision-making depend on the quality of data, not quantity, Kanter said.
Without tools or expertise to eliminate minutiae or select only relevant classes of information, the only alternative most companies would have is to hire forensic accountants or other data experts to spend hours or days filtering big data by hand--a process far more expensive, imprecise, and un-repeatable than using software designed to do the same thing in a fraction of the time, without the risk that perceptual biases will warp the analysis.
The fastest-growing categories, however, are those designed for specific vertical markets such as healthcare and finance, and those aimed at collecting and analyzing data for specific departments within the organization, such as marketing, IT, and customer service.
Though many are traditional on-site apps, most are appearing as online apps built on cloud platforms with the computing power to analyze huge data sets as well as the algorithms to find useful knowledge within masses of data, according to Raj De Datta, CEO of BloomReach.
"BDAs [big-data apps] don't just repackage your data in a cool interface or offer productivity improvements in data scalability, they harness the world's data to deliver you a better outcome--like more revenue," according to De Datta.
BDAs, publicly available at subscription prices rather than the full cost of licensing and implementing sophisticated analytics on-premise, could make big-data analysis available to vast numbers of mid-sized companies that lack the will or expertise to build their own tools.
It only means that the organization's data-handling practices are not prepped to give decision makers the data they need when they need it to make better decisions, which would lead them to see decisions based on big data--and therefore big data itself--as a strategic advantage worth pursuing, Nangia said.
The challenge for big-data advocates--as it is with many promising but early-stage technologies--is to demonstrate quickly the benefit of building complex data sets and analytics to help their companies make better decisions, and get top managers to agree to make the investment even without the heavily analyzed data that might help push them in the right direction, Castro said.
"There's still a lot of convincing to be done," he said.
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