IEEE Spectrum August, 2015 - 29

TEChnICaLLY SPEaKInG_bY PaUL McfEdRIES

OPInIOn

We're All DAtA Geeks NoW
Data science is going to be as foundational to
education as English... [It] doesn't belong in the
business school. Everybody should take data
science. -Jennifer Priestly, Kennesaw State University
W h en Ga rt n er r el e a sed i ts a n n ua l Hype Cycle for Emerging

Technologies for 2014, it was interesting to note that big data was now
located on the downslope from the "Peak of Inflated Expectations," while
the Internet of Things (often shortened to IoT ) was right at the peak,
and data science was on the upslope. This felt intuitively right. First, although big
data-those massive amounts of information that require special techniques to store,
search, and analyze-remains a thriving and much-discussed area, it's no longer the
new kid on the data block. Second, everyone expects that the data sets generated by
the Internet of Things will be even more impressive than today's big-data collections.
And third, collecting data is one significant challenge, but analyzing and extracting
knowledge from it is quite another, and the purview of data science. Just how much
information are we talking about here? Estimates vary widely, but big-data buffs sometimes speak of storage in units of brontobytes, a term that appears to be based on
brontosaurus, one of the largest creatures ever to rattle the Earth. That tells you we're
dealing with a big number, but just how much data could reside in a brontobyte?
I could tell you that it's 1,000 yottabytes, but that likely won't help. Instead, think of
a terabyte, which these days represents an average-size hard drive. Well, you would
need 1,000,000,000,000,000 (a thousand trillion) of them to fill a brontobyte. Oh,
and for the record, yes, there's an even larger unit tossed around by big-data mavens:
the geopbyte, which is 1,000 brontobytes. Whatever the term, we're really dealing
in hellabytes, that is, a helluva lot of data.
Wrangling even petabyte-size data

IllustratIon by

Greg Mably

sets (a petabyte is 1,000 terabytes) and
data lakes (data stored and readily accessible in its pure, unprocessed state) are
tasks for professionals, so not only are listings for big-data-related jobs thick on the
ground but the job titles themselves now
display a pleasing variety: companies are
looking for data architects (specialists in
building data models), data custodians
and data stewards (who manage data
sources), data visualizers (who can
translate data into visual form), data
change agents and data explorers
(who change how a company does business based on analyzing company data),
and even data frackers (who use enhanced or hidden measures to extract or
obtain data).
But it's not just data professionals who
are taking advantage of Brobdingnagian
data sets to get ahead. Nowhere is that
more evident than in the news, where a
new type of journalism has emerged that
uses statistics, programming, and other
digital data and tools to produce or shape
news stories. This data journalism
(or data-driven journalism) is exemplified by Nate Silver's FiveThirtyEight site,
a wildly popular exercise in precision
journalism and computer- assisted
reporting (or CAR).
And everyone, professional and amateur alike, no longer has the luxury of dealing with just "big" data. Now there is also
thick data (which combines both quantitative and qualitative analysis), long data
(which extends back in time hundreds or
thousands of years), hot data (which is
used constantly, meaning it must be easily and quickly accessible), and cold data
(which is used relatively infrequently, so
it can be less readily available).
In the 1980s we were told we needed
cultural literacy. Perhaps now we need
big-data literacy, not necessarily to
become proficient in analyzing large
data sets but to become aware of how
our everyday actions-our small data-
contribute to many different big-data sets
and what impact that might have on our
privacy and security. Let's learn how to
become custodians of our own data. n

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Table of Contents for the Digital Edition of IEEE Spectrum August, 2015