Big Data

Moving from Analyzing Datasets to Decisions in DPL

We've discussed "Big Data" within our Imperfect Information blog in the past -- with a moderately critical tone. (See Big Data and DA) When it comes to Big Data us DA folks think far too much emphasis is put on the past and how many terabytes one can unearth and not the value (or lack thereof) that the wodges of data can bring to your decisions.

Mine's Bigger than Yours!

Is it just me, or is there a kind of schoolboy competition emerging in certain quarters of the analytics community, particularly those where Big Data is revered? Take this tweet from the normally level-headed INFORMS CAP people:

Well Said: Reid Hoffman on Data and Probability

In a recent interview, Reid Hoffman, co-founder and executive chairman of LinkedIn speaks about the nature of data and probability.

"We live in a probabilistic universe, and we tend to think in determinist ways. If A is data-driven and I think I have that data, how certain am I that I have that data? What could I discover that might actually tell me that that data is formulated wrongly? When you dig into it, most of your arguments are actually probabilistic. They're not certain, even when you have data. You're really trying to get a sense of whether you have a reasonable bet on the probability."

Big Data and Decision Analysis: From Data to Information to Decision Quality

Most decision analysts greet "Big Data" with considerable scepticism. Eyes roll, arms are crossed, someone mumbles something about driving while looking in the rear view mirror. It's safe to say Big Data hasn't been welcomed with open arms by the DA community.

When some new/rebranded management science thing comes along, we can react in one of several ways:

   0. This thing is worthless rubbish.
   1. This thing isn't new, we've been doing this all along.

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