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Data can’t account for everything in our experience, nor serve as the only guide for our thinking, planning and decision-making. janlgordon's insight:This piece is from the NY Times and raises some important issues about the way we measure data. I selected it because it talks about the strengths and limitations of data analysis.'The big novelty of this historic moment is that our lives are now mediated through data-collecting computers" says David Brooks, the author of this article..He goes on to say........**In this world, data can be used to make sense of mind-bogglingly complex situations.**Data can help compensate for our overconfidence in our own intuitions and can help reduce the extent to which our desires distort our perceptions."But there are many things big data does poorly. Let’s note a few in rapid-fire fashion" Here's what caught my attention:**Data struggles with context. Human decisions are not discrete events. They are embedded in sequences and contexts**People are really good at telling stories that weave together multiple causes and multiple contexts.**Data analysis is pretty bad at narrative and emergent thinking, and it cannot match the explanatory suppleness of even a mediocre novel.**Data obscures values. The author says: I recently saw an academic book with the excellent title, “ ‘Raw Data’ Is an Oxymoron.” **One of the points was that data is never raw; it’s always structured according to somebody’s predispositions and values.**The end result looks disinterested, but, in reality, there are value choices all the way through, from construction to interpretation.Takeaway:**This is not to argue that big data isn’t a great tool. It’s just that, like any tool, it’s good at some things and not at others. Selected by Jan Gordon covering "Curation, Social Business and Beyond"Read full article here: [See it on Scoop.it, via Curation, Social Business and Beyond