As IIA sees it, analytics 1.0 largely involves descriptive analytics that comes from small sets of internal, structured data, Research Director Thomas Davenport says. Resulting reports tend to stay within IT departments, away from decision makers, and look back, not ahead.
Analytics 2.0 considers complex, large and unstructured data sets and develops products (not reports) that make information readily accessible. This represents the heart and soul of big data startup activity, he says, but remains largely confined to Silicon Valley.
Finally, analytics 3.0 bridges traditional analytics and big data, using “rapid, agile insight delivery” to put analytics tools at the point of decision. Examples include LinkedIn’s “People You May Know” and “Jobs You May Be Interested In” features, Davenport says.