Turn Big Data into Smart Data: You’ll Have Happier Customers

Predictive analytics expert Ingo Mierswa, who also happens to be CEO and founder of RapidMiner, recently blogged about the relationship between big data and smart data. The true power of big data, he explains, lies in creatively using advanced analytics to transform that 'big' data into 'smart' data and actionable business intelligence.

Why Is Big Data Such a Big Deal?

First, Mierswa points out, big data can be defined in terms of the "3 Vs" that Gartner's analysts have enumerated -- Volume, Velocity, and Variety. We're talking about really large volumes of data, and different kinds of data (some structured, some unstructured, etc.), possibly collected in batch mode, at intervals, and/or in real-time (that's the velocity component).

Volume, of course, is the most obvious characteristic of big data. The sheer volume of big data makes it hard to store and hard to retrieve. But Mierswa points out that its size is actually the least interesting quality of big data.

"The technology needed to store and retrieve this massive amount of data is coming along quickly, building on past developments like relational database systems and storage clusters. Now NoSQL databases and Hadoop are considered solid solutions for distributed data storage and retrieval." And, Mierswa predicts that many more companies will soon be using these technologies as underlying data delivery frameworks.

It's actually the variety of big data -- whether it's structured and/or unstructured -- that adds another layer of complication on top of the usual storage and retrieval challenges. One of the key challenges, Mierswa suggests, is organization. "Big data is fundamentally hard to organize." He points out that when you move beyond analyzing just structured data, you may, for example, "need text analytics to transform unstructured information like text, images, or videos into structured data."

Big Data Alone Has No Value

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