by Angela Guess
R Wang of Software Insider recently opined, “The hype around big data has crescendoed to the levels of SOA in the early 2000′s, cloud in the late 2000′s, and social in the past few years. Unfortunately the hype is creating three main pitfalls: (1) A morass of confused definitions. In fact a quick survey of any educated audience, yields a multitude of definitions. Some folks see big data as large data sets and data warehouses, others see big data as code for analytics and BI. Many see the output of big data as infographics or the hardware behind the support of big data. The V’s of big data continue to expand from volume, velocity, and variety to include veracity, viscosity, and virality. Some folks even have 16 V’s in their definitions.”
The list continues: ” (2) Solutions confusion among buyers. A technology vendor land grab for mind share with big data is happening now the same way everyone adopted cloud. Hardware vendors now enable big data. Storage providers now deliver big data solutions. Integration vendors provide plumbing and intelligent connections for big data. Analytical vendors now all support big data. Some folks like to confuse Hadoop with big data. Everyone has a solution, just not the solution a buyer thinks they need. Confused capabilities continue to proliferate amidst a lack of good customer references. Customers feel the chaos. (3) Discussion on technology options not business problems. The discussion about big data has evolved into a technology conversation not a business value or transformation conversation. Clients immediately talk about products and technologies without defining the problem to be solved. Technology investments take over the discussions on solution development.”
Read Wang’s recommendations for these problems here.
