New Paths to Data Integration: Taming Big Data Helps Address Lingering Issues

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Big Data, Big Prize

To a large extent, the integration woes that come from increased complexity are not the fault of big data—they are the same issues that have plagued enterprises for many years. Big data just adds a big, scary term to an already existing problem, says Diana. “Big data hype is complicating things—it is distracting from the true story,” he explains. “Big data is simply an evolution of information management.”

Or, conversely, the fear of big data’s purported bigness is causing some organizations to throw too much unnecessary technology at the challenge. “Many businesses think their data is big and therefore requires big data tools,” says John Lucker, principal with Deloitte Consulting. “They think the panacea is to buy software to address big data. They think addressing big data requires a much more rigorous examination of information management and analytic strategy. People need to carefully sift through the sizzle versus the drivel.”

The bottom line is that integration challenges arise whether data is big data or not. Some sources of frustration include “inconsistent data formats, geographical data source distribution and the variable forms of data and their multiple sources,” Oleg Komissarov, senior vice president of DataArt, tells DBTA. “Data systems are often built without a specific data strategy. Building a single informational field in such organizations is challenging. There are no silver bullets that exist allowing you to build data systems providing excellent data quality, governance, and super-fast search capabilities and data availability in combination with low-cost support. It takes a lot of work to do that.”

The key is not to obsess about the bigness of big data, Lucker advises. Instead, integration efforts should focus on “what is truly important and why, how it will serve the business, what is the short, medium, and long-term value,” he says.

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