A DRIP Problem?

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Data rich but information poor (DRIP) is killing us.

Natural or man-made disasters (think hurricane or drunk driving) could be avoided if weather data can be transformed into information in a timely fashion.   Proliferation of data sensors (e.g. smartphones, tablets, social networks, etc.) yield lots of data.  Unfortunately, turning these data into information still lags.

The ever growing volume of data requires (1) recording capacities and (2) analyzing capabilities.  The capacity question can be further divided into capturing and storage facilities.  Both facilities are relatively easy as compared to the need for analyzing capabilities.

Analyses can’t not be done by computers.  They require human interventions.  Given enough data, one can draw correlations with anything (like shoe size to intelligence) regardless if a causal relationship exists or not.

Human interpretation is necessary in interpreting meaningful trends and plausible parameters.  Artificial intelligence has come a long way, but alone it is not enough. To combat the DRIP problem and start to turning data into information, we need more data scientists.


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