by Angela Guess
Dan Kusnetzky recently wrote in SearchDataCenter, “From a data center perspective, Internet of Things and big data projects almost always stress the network and storage infrastructure. Planners need to carefully assess infrastructure requirements before their organization embarks on these sorts of large-scale, data-intensive projects. Traditional business intelligence projects are founded in needs and understandings that differ from those of big data projects. A typical business intelligence effort starts with a clear idea of what questions must be answered; what data is available or must be collected to answer those questions; what results must be reported; and who within the organization needs those results… Internet of Things (IoT) and big data initiatives have a different focus. They ask: What are the right questions; what are the problems to address to better serve customers; and what products must be made available to retain current customers while enticing new customers to purchase products and services from the company?”
He goes on, “This typically means that IoT and big data projects require different expertise, different levels of experience and different tools. As a result, such projects can be more difficult for an IT team to execute. When powerful new technologies or new approaches to IT gain a certain momentum, there can be a rush to adopt them — sometimes with little understanding of what is required to have a successful first experience. IoT and big data clearly fall into this category. This thinking can drive organizations to invest heavily in an approach that yields much disappointment and little useful data.”
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