[Wikimedia-l] "Big data" benefits and limitations (relevance: WMF editor engagement, fundraising, and HR practices)

Strainu strainu10 at gmail.com
Mon Dec 31 14:19:25 UTC 2012

Hi Pine,

It might be because of the alcohol I've ingested these last days, but
- what are you proposing exactly?

Hapy new year,

2012/12/30, ENWP Pine <deyntestiss at hotmail.com>:
> I'm sending this to Wikimedia-l, Wikitech-l, and Research-l in case other
> people in the Wikimedia movement or staff are interested in "big data" as it
> relates to Wikimedia. I hope that those who are interested in discussions
> about WMF editor engagement efforts, WMF fundraising, or WMF HR practices
> will also find that this email interests them. Feel free to skip straight to
> the links in the latter portion of this email if you're already familiar
> with "big data" and its analysis and if you just want to see what other
> people are writing about the subject.
> * Introductory comments / my personal opinion
> "Big data" refers to large quantities of information that are so large that
> they are difficult to analyze and may not be related internally in an
> obvious way. See https://en.wikipedia.org/wiki/Big_data
> I think that most of us would agree that moving much of an organization's
> information into "the Cloud", and/or directing people to analyze massive
> quantities of information, will not automatically result in better, or even
> good, decisions based on that information. Also, I think that most of us
> would agree that bigger and/or more accessible quantities of data does not
> necessarily imply that the data are more accurate or more relevant for a
> particular purpose. Another concern is the possibility of unwelcome
> intrusions into sensitive information, including the possibility of data
> breaches; imagine the possible consequences if a hacker broke into
> supposedly secure databases held by Facebook or the Securities and Exchange
> Commission.
> We have an enormous quantity of data on Wikimedia projects, and many ways
> that we can examine those data. As this  Dilbert strip points out, context
> is important, and looking at statistics devoid of their larger contexts can
> be problematic. http://dilbert.com/strips/comic/1993-02-07/
> Since data analysis is also something that Wikipedia does in the areas I
> mentioned previously, I'm passing along a few links for those who may be
> interested about the benefits and limitations of big data.
> * Links:
> From the Harvard Business Review
> http://hbr.org/2012/04/good-data-wont-guarantee-good-decisions/ar/1
> From the New York Times
> https://www.nytimes.com/2012/12/30/technology/big-data-is-great-but-dont-forget-intuition.html
> and
> https://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html
> From the Wall Street Journal. This may be especially interesting to those
> who are participating in the discussions on Wikimedia-l regarding how
> Wikimedia selects, pays, and manages its staff.
> http://online.wsj.com/article/SB10000872396390443890304578006252019616768.html
> And from English Wikipedia (:
> https://en.wikipedia.org/wiki/Big_data
> and
> https://en.wikipedia.org/wiki/Data_mining
> and
> https://en.wikipedia.org/wiki/Business_intelligence
> Cheers,
> Pine
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