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Gartner: Big Data Spending to Reach $28 Billion This Year

October 18, 2012
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Market research firm Gartner predicts that enterprises will spend $28 billion on Big Data this year, climbing up to $34 billion next year. However, it believes the buzzword will phase out by 2020 when Big Data will have become the new normal.

“Because big data’s effects are pervasive, big data will evolve to become a standardized requirement in leading information architectural practices, forcing older practices and technology into early obsolescence,” said Gartner’s Mark Beyer in a press release. “As a result, big data will once again become ‘just data’ by 2020 and architectural approaches, infrastructure and hardware/software that does not adapt to this ‘new normal’ will be retired. Organizations resisting this change will suffer severe economic impacts.”

Big data is a big deal,” wrote InformationWeek’s Kevin Fogarty. “Marketers and corporate strategists hope it can provide insights on customers, while IT managers struggle with how to manage all that data within the parameters of their budget and staff. What IT professionals will do, according to a Gartner study published today, is spend nearly half of all IT resources during the next few years in an effort to adapt large, complex IT infrastructures to the demands of big data projects.”

In eWeek, Nathan Eddy observed, “The most significant impact big data currently has is in social network analysis and content analytics, representing 45 percent of new spending each year. Only $4.3 billion in software sales will be driven directly by demands for new big data functionality in 2012, while adapting traditional solutions to the demands of big data currently drive the majority of spending, the report noted.”

TechCrunch’s Alex Williams said the report concluded, “Big data is not a distinct market. More so, data is everywhere, impacting business in any imaginable way. Its influx will force a change in products, practices and solutions. The change is so rapid that companies may have to retire early existing solutions that are not up to par.”

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