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Getting a jump on Big Data

Getting a jump on Big Data

By:  Vawn Himmelsbach  On: 28 Oct 2011 For: ComputerWorld Canada Creator

PREMIER BUSINESS LEADERSHIP SERIES In-memory analytics on a database appliance will bring analysis of huge bodies of data closer to real time, according to SAS

ORLANDO — Run-intensive analytic tasks that used to take hours or days can now be run in a couple of minutes. At the Premier Business Leadership Series behind held here this week, SAS announced its High-Performance Analytics, which can handle terabytes of data in near real-time.

Available in mid-December, High-Performance Analytics will meld SAS’s analytics technology with in-memory processing on Teradata or EMC Greenplum database appliances.

“That’s what we’re starting to think about with Big Data, doing things closer to real time,” said James Adamczyk, CTO of Accenture Software.

Most companies have decided what data they want to use for analytics, and that’s the only data they use. Now there’s a need to do real-time analytics against both structured and unstructured data.

“With this notion of linking into social media and other forms of data, when a customer links to your Facebook page, now you’ve got data that you didn’t have anything to do with,” said Adamczyk.

The next step is overlaying this data and mining it. “I don’t know of a lot of companies that have really thought that through about how they’re going to do that,” he said.

Of 258 North American business leaders surveyed by the Accenture SAS Analytics Group, 72 per cent indicated they would increase spending on business analytics in 2012 compared to 2011, although 60 per cent said they are missing the right analytical business skills, technical skills or both, and just 22 per cent said their analytics are integrated across their entire organization.

About two-thirds of organizations are “data wasters” and not using the full potential of their data, said Michael Singer, senior editor of technology with the Economist Intelligence Unit. Typically, this is because they’re looking at the same types of information; those who’ve overcome this have figured out how to integrate their data and coming at it from a different perspective.

Added to this quagmire of Big Data is machine-to-machine data, such as sensor networks. “They can’t get number crunching done fast enough,” said Singer. “The problem is they’re collecting almost too much data, they don’t want to throw anything out, but there’s this huge long tail of information that most companies are still struggling with.”

Big Data is really about unlocking business value from the vast amount of unstructured and multi-structured data out there.

“It’s exciting in a lot of ways, but we’re all trying to make sense of it,” said Maura Hart, CIO of Winn-Dixie. “Our leadership team certainly sees the business value from the investments we’ve made to date and the importance of analytics in our business, but there’s a change in how we need to react.” Internal customers want data as near real time as they can get, she said.


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vawn himmelsbach Vawn Himmelsbach is a Toronto-based journalist and regular contributor to IT World Canada's publications. She also writes about travel and runs the Web site http://GlobalNomad.ca.
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