Grace Hopper talk options.

A friend suggested I propose a talk at Grace Hopper this year.  She was thinking I could do a sort of introduction to data visualization (which I already outlined for my Analytics department shortly before I left).  I feel like there are more suitable women for giving a lecture on that, but maybe I’m not giving myself enough credit.  I’m sure “not giving yourself enough credit” is a common theme at Grace Hopper!

Here are some topic ideas, one educational, one personal-inspirational, and one idea-inspirational.  What do you guys think I should talk about?

Introduction to Data Visualization (Data Science track)
I’ve been paid to work on the programmatic visualization of abstract data since 2005 (doing it for personal use since…1999?), so I can give people some solid advice, but I’m not always up on the latest research.  Most of the time in industry, though, the latest sexy thing is not useful.  This is almost as true in data visualization as it is in machine learning (Seriously…the regression model or equivalent is the best choice at least 90% of the time.)  So I’m sure I can cover all the crucial pieces for an intro course.  The upside of this option is that I’ve got an outline lying around somewhere from a lecture I was going to give at my previous job.

Straight From Lower-middle Management to Tech Founder (Career track)
This would be a my personal story with observations, anecdotes and advice.  I can’t guarantee it will be a complete success story, but it’s been a very interesting process for me, and puts my previous experiences in a different light where my gender probably made more difference than I thought.  Quite relevant for the conference.

Social Analytics: So Much More We Can Do (Career or Data Science track)
Many of you know I’ve been thinking about personal social analytics for a long time, and I spent a lot of time thinking about social analytics for the dating sites I worked on at my previous company.  I can talk about the popularity of social media and the minimal analytics they provide, and of course mention Klout and its strengths and weaknesses.  And I can talk about Google Analytics and CRMs.  And then, I can talk about what isn’t on the market.

My open source project only got so far before I put it on hold in favor of other work, but I’ve been brainstorming a lot of possibilities for analyzing personal conversation history in the last decade and a half.  These ideas have all been feasible during that time, and they’re getting faster to compute and easier to scale all the time.  So why isn’t anyone making it happen?  In my experience, social media users have been very excited with any level of navel-gazing: finding the list of people who follow them that they don’t follow, or the other way around (drama!); seeing who talks to them the most on a given platform; etc.  There is a market that would pay just for increased analytical power! And they’d definitely pay to have all of their communications data integrated into one location for analysis or even plain review.

And a lot more can be done with the same data.  Merely extend it with some labels and charts and BAM! Social productivity tool.  New target market.  Extend that with some very basic recommendation capabilities and BAM! Customer management tool.  Another target market.  If I thought of all this at least a decade ago, straight from college and before I ever heard of social analytics, others must have too.  Why isn’t the market filled with options?

sudo make me a proper social analytics platform!

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