Database Reference
In-Depth Information
Gutierrez:
Does Quid use itself internally to understand where it should grow,
what the next challenges facing it will be, and what it should be developing?
Heineike:
Yes, we've definitely looked at and asked a lot of questions about
ourselves, as we like to be very meta. We've used our product internally to
analyze the big data space and see who all the startups in our space are, and
whom we are the most similar to. We've used it to research technologies
we're thinking of using, and to get up to speed on new algorithms and method-
ologies. So yes, we have absolutely used it and have found it useful to analyze
ourselves and our industry.
I have also analyzed data science in the past to find out what the news in data
science talks about. What I found, which is fascinating, is that it's a lot of big
vendors—vendors of data platforms, basically—are the ones who drive a lot
of the conversation. And then you find a few companies who've done a really
good job of positioning themselves and their products. These companies are
mainly LinkedIn, Facebook, and Twitter. So there is a conversation driven by
them talking about products they've built and why they're interesting.
And finally there's this hubbub in the middle of everyone else going, “What
the heck is data science? What kinds of skills are needed? What kind of teams
should be built?”
Gutierrez:
Are there any publications, websites, conferences, or blogs some-
one interested in learning more about your space should look into?
Heineike:
We're bringing together information on data viz, deep learning,
data science, and how it is being used, on quid.com/insights, which you can
look into.
Outside of Quid, I've found Twitter very useful for keeping up with what's
happening. There are a lot of interesting people from a wide range of different
viewpoints who tweet links to different links and references that are good to
be aware of. Some of them are journalists from places like
The Guardian
and
some of them are organizations like the Stanford NLP group. For example,
Simon Rogers, who was with
The Guardian
and has now moved to Twitter,
posts links to different visualizations. Stanford NLP, post links to recent text
mining research.
There are also creative people who use data in imaginative ways. For example,
Pete Warden who just released a software development toolkit that lets lever-
age deep learning in smartphone apps. You can basically set it up to make it
easy for you to create a mobile app that uses deep learning in the background.
There's a wonderful video on his blog of him making his app detect whether
his cat Dude is in the picture or not.
So for me, it's been important to piece together these people from different
kinds of domains, to be able to get ideas and inspiration from them.
