Database Reference
In-Depth Information
provide powerful insights both to nonprofits and to any industry where data
is not being used to its full potential. What is ultimately inspiring at the end of
the day is that together we really can make an impact.
Gutierrez:
For people who are up-and-coming, what is something they
should really understand?
Hu:
A couple things. First is that you definitely have to tell a story. At the end
of the day, what you are doing is really digging into the fundamentals of how
a system or an organization or an industry works. But for it be useful and
understandable to people, you have to tell a story.
Being able to write about what you do and being able to speak about your
work is very critical. Also worth understanding is that you should maybe
worry less about what algorithm you are using. More data or better data beats
a better algorithm, so if you can set up a way for you to analyze and get a lot
of good, clean, useful data—great!
Gutierrez:
For an organization that is just starting the data collection, how
would you convey to them how to capture this data correctly or how to
encode it correctly?
Hu:
That is a really tricky question. I think intelligent storing of data is some-
thing that maybe people do not think about, because when they're acquiring
this data, they're not anticipating how the data science components will fit
and what they can do with it. So as data science becomes more popular and
important, having those institutions in place whereby you are getting the data
you need is really critical. Unfortunately, I think it is hard to know what you
really need until you dig into it. So I do not fault anybody for realizing halfway
through a project that they do not have the data they need. That happens a
large chunk of the time, even dealing with what we do at Next Big Sound. But
it is about recognizing that as early as you can, so maybe going through and
actually thinking about what you want to do and figuring out whether you
have that data and acquiring it of you don't.
At Next Big Sound, we've been tracking social media since 2009, and the
only reason why we can do the types of cross-sectional analyses that we
do is because we have that data. Nobody else has several years of daily data
recordings of each artist, or the number of Facebook fans they are getting on
a particular day, or how many YouTube plays they are getting. You really just
have to think carefully about what you want to do ahead of time.
Gutierrez:
Just the data set alone is a very valuable asset?
Hu:
Correct. A great deal of the value that we provided is based on the data
we have. Further, we have a dashboard that allows you to see all of your data
all in one place. That is something that I have learned as well—simply having
all of your data in one place, easily accessible, easily queryable about different
questions—that in and of itself is extremely valuable to a large majority of
