According to a Gartner’s report on big data adoption in 2013, 64 percent of organizations have already invested in or plan to invest in Big Data technology, with 34 percent planning to invest within the next year or two. In the Gartner big data study, information and business leaders most often associate the term opportunity with big data. This positive perception undoubtedly translates to increased investments in and adoption of big data technology. While there is general consensus that engagement with big data is necessary for enterprises to remain competitive, few people have considered the pitfalls of rushing into the big data madness without a long-term perspective. Jim Kaskade, the CEO of Infochimps, offers five maladaptive practices that businesses must avoid when it comes to their organization’s big data adoption.
Do it all at once. It’s an evolution, not a revolution. Any solution designed to solve all your problems will inevitably yield a series of disappointments. Try identifying a very specific business challenge to address with Big Data, solve it, and expand and iterate your program step-by-step.
House your own data. 10 terabytes of legacy infrastructure costs $1M or more to store the warehouse for any major company will be larger than 20 terabytes. That’s expensive. Instead of housing your own data, partner with an expert who can guide you through a hybrid deployment strategy that leverages a public, virtual private or private cloud.
Rest all hopes on Hadoop. Hadoop, which performs historical batch processing, gets 80% of the Big Data attention, but it’s only 20% of the solution. For a truly customer-centric view, tie together historical, real-time and near real-time data.
