Capgemini and Enterprise Management Associates (EMA) both recently published reports that suggest most enterprises recognize the importance of big data analytics, but aren’t yet fully satisfied with the results of them so far.
That’s not to say they aren’t learning how to achieve success. EMA Managing Research Director John L. Myers observes: “Companies were still understanding what data was and where they could collect it from. Over the last two years, organizations have now assimilated what data can do.”
Some 60 percent of executives believe big data will disrupt their industry within the next three years, even though 67 percent lack consistent criteria they can use to assess their existing initiatives.
Capgemini says that there are a number of barriers that need to be overcome before enterprises can make a success of big data projects. Information is still is scattered in silos across different parts of the enterprise, with nearly four-fifths of organizations still to integrate their data sources.
In addition, best practices from successful implementations are not shared within the organization, initiatives are not prioritized and resources are not deployed in the most effective ways.
These factors leave company decision makers unable to make accurate and timely decisions on the basis of data – after all, which set of non-integrated data is the most reliable?
“A significant number of organizations operate with scattered pockets of analytics resources or with decentralized teams that function without any central planning and oversight,” Capgemini warns.
increasing number of projects
Despite these challenges there has been a significant increase in the number of companies running big data projects. One of the drivers is the growth of machine-generated data.
EMA notes that the use of human-sourced data fell from 45.4% to 30.9% between 2012 and 2014, while machine-generated data jumped from 23.7% of projects to 41.2% of projects in the same period. It said that 63% of respondents are working on an Internet of Things big data project.
The ultimate goal of most big data projects remains the same: “People want to make decisions fast, predict customer behavior more quickly, and react more quickly to events in the real world,” said Dr. Barry Devlin, founder and principal of 9sight Consulting who collaborated with the EMA (Forbes).
Those companies that do succeed include those who successfully manage transformation of their technical and political silos. Automation and digital transformation will be critical in unlocking success in big data projects, while Capgemini calls for the creation of big data champions across organizations, tasked with energizing these projects.
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Jon Evans is highly experienced technology journalist and editor. He has been writing for a living since 1994. These days you might read his daily regular Computerworld AppleHolic and opinion columns. Jon is also technology editor for men’s interest magazine, Calibre Quarterly, and news editor for MacFormat magazine, which is the biggest UK Mac title. He's really interested in the impact of technology on the creative spark at the heart of the human experience. In 2010 he won an American Society of Business Publication Editors (Azbee) Award for his work at Computerworld.