Database Reference
In-Depth Information
As for conferences, the Strata conference is, I think, one of the biggest ones.
The O'Reilly team does a really good job of bringing together a mix of people
from different kinds of problem domains and different kinds of views of what
data science is and what the issues in big data are. So they've put together
some really fascinating conferences.
Data science is very broad, and so there aren't really just one or two publica-
tions that speak to it, and that's why we end up with this kind of massively
complicated Twitter feed of people from all over the place chiming in with
different bits and pieces. If you could meld them together, then you can get
something really interesting.
Gutierrez:
You mentioned that you put together yourTwitter feed to encom-
pass different viewpoints. What are some good examples?
Heineike:
I've got people from different kinds of academic disciplines, which
means different kinds of methodological ideas. So the viewpoints encompass
“How would I go about doing this?” There are a couple of people that I like
for having different viewpoints on the data industry as a whole.
One of those is Kate Crawford, who is a researcher with Microsoft Research.
She did a great keynote at Strata with a follow-up essay in the
Harvard Business
Review
,
1
in which she talked about making sure that you're sufficiently skep-
tical of your own data. They did an analysis of Hurricane Sandy and they
found that—by looking at Twitter data—pretty much everything happened
in Manhattan. Then they were like, “Well, no, not everything happened in
Manhattan. Actually, it's just that people who live in Manhattan tweet a lot
more than people who live down the coast.” So the key message was to really
think about your data and how it's being generated, as evidenced by what they
found out about the hurricane and what happened just based on Twitter data
analysis.
Another person is Kenneth Cukier, who is
The Economist
is big data editor. He
co-wrote a book called
Big Data: A Revolution That Will Transform How We Live,
Work, and Think
that's given me a lot of thoughts to mull over regarding the
direction that the industry's going.
2
So it's good to have these voices that chal-
lenge you a little bit.
1
Kate Crawford, “The Hidden Biases of Big Data,” Harvard Business Review, April 1, 2013,
2
Kenneth Cukier and Viktor Mayer-Schönberger,
Big Data: A Revolution That Will Transform
How We Live, Work, and Think
(Houghton Mifflin Harcourt, 2013).
