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A TDWI report notes that there is a serious shortage of skilled professionals, which limits the adoption of big data analytics. Currently, there are more people trained in the old-school data warehousing methodologies than in big data analytics, and they use different skill sets. As a result, there is a lack of support for bringing newer tools and techniques into companies.
As for early adoption issues are concerned, there may be some initial difficulties with staff getting up-to-speed with the new technology. As with anything in tech, there's always a bleeding edge before the cutting edge. The tools are more refined now than just a couple of years ago, and what's more likely to happen now is that early adopters now will find innovative ways to use this technology to expand their business and dominate markets. For instance, using Sybase in-memory databases, analytics is applied to data in memory rather than through a separate application, which means extrapolating meaningful results in near-to-real time. This generates far more accurate predictions of future events and the underlying trends that lead to these predictions.