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October 2016, Volume 4, Number 5

Big data architectures face big hurdles with technology integration

IT teams looking to build big data architectures have an abundance of technology choices they can mix and match to meet their data processing and analytics needs. But there's a downside to that: Putting all the required pieces together is a daunting task. Finding and deploying the right big data technologies within the expanding Hadoop ecosystem is a lengthy process frequently measured in years, unless corporate executives throw ample amounts of money and resources at projects to speed them up. Missteps are common, and one company's architectural blueprint won't necessarily translate to other organizations, even in the same industry. "I tell people that it's not something you can order from Amazon or get from the Apple Store," said Bryan Lari, director of institutional analytics at the University of Texas MD Anderson Cancer Center in Houston. Fully constructing a big data architecture, he added, "is complex, and it's a journey. It's not something we're going to implement in six months or a year." Nor is there an easy-to-apply ...

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