Hello, welcome and good evening
my name is Phil Nuzhdin, I'm an
alumnus of the Stern School
of Business, undergraduate
class of 2012.
I also serve on the NYU
Stern Alumni Council as
vice chair of signature events.
I'm excited to be here tonight
with you this evening
for very incredible program. It's
great to see so many alumni
come out to this event and I'm
happy to see and recognize a
few faces.
It's my distinct pleasure to
introduce Kristen Sosulski
author of the recently published
book Data Visualization Made
Simple, Insights into Becoming
Visual, in conversation this evening
with Helen Todd, co founder and
CEO of Sociality Squared.
Professor Sosulski joined NYU
Stern in 2011 and is
currently the clinical associate
professor of information systems
and the director of learning
science lab where she develops
immersive online learning
environments for the business
school education. Since 1999
Kristen has been
developing digital online
learning experience experiences
for college students first
at Columbia University and now
at Stern and she's the author
of two previous books, Essentials
of Online Course design, a
standards based guide and the
Savvy Students Guide to Online
Learning.
Kristen has taught both MBA
students and professional
executives data
Visualization, computer
Programming, and business
operations throughout the world
including New York and Shanghai
and Panama. Her area of expertise
lies in learning science
technology and data
visualization which you won't
find surprising
given the title of her new book.
Our moderator this evening is
Helen Todd, co founder and
CEO of Sociality Squared a full
service social media agency that
helps brands harness the power
of social media to increase our
online reach and build loyal
communities.
Helen confounded Sociality
Squared in 2010
to help brands leverage the
power of word of mouth and
content, thank you both
for being here this evening.
Data Visualization Made Simple
was published by Routledge just
a few weeks ago and is sure to
be a favorite amongst academics
and industry experts alike, this
book is a practical guide to
the fundamental strategies and
real world cases for data
visualization an essential
skill required in today's
information rich world.
After the talk we hope that you
will join us as we continue the
conversation during a reception
and book signing right here in
this room and now please allow
me to hand over the stage
to Kristen and Helen.
Todd: It's such an honor to be here
and the social media person
inside of me has to also point
out the hashtag for the evening
is #becomingvisual
but yeah back in 2010 that
I actually got to meet Kristen
and spoke of the classroom is
such an honor to be on stage
with you here tonight. Sosulski: Oh my gosh
Helen this is
this is terrific and I'm so
happy I wouldn't want anyone
else to be here is so
you know do you know that you
were the first CEO that I
brought
into my Stern classroom?
Todd: Not until I looked at my
notes for this talk tonight.
Yeah I know I looked in my
emails and
then we got to work together in
2016 and that was
really the kernel of the idea for
this book and it's been so
wonderful to get to see it come
full circle from an idea and a
lot of people have ideas but not
all ideas turn into physical
things and we're in for a
special treat because everyone
will get to see the book at the
same time for the first time tonight
including Kristen,
so get a special in boxing. But
let's dive into why we're here
we're here to talk about data
visualization so what was your aha
moment that got you into this?
Sosulski: So, like many of us my aha
moment came in grad school.
So I thought that I tell a
little story about how this came
to be so I have a few slides but I was
at Columbia University and
I was studying for my doctorate
and I was working with a
professor who wanted to figure
out how he could teach
aspects of the building suspense
in a film,
like what, I'm an Ed major, like
I've no idea about this and so
that was that was their driving
question how could he show
students that that actual
structural elements of film like
actually literally where the
camera is
can actually build suspense in a
movie.
So I got to watch
lots of
movies when I was in grad school
and we decided to pick a scene
from a famous movie, Alfred
Hitchcock's 1960
Psycho, how many people have
seen the movie?
All right, this will be easy
So do you remember seeing where
Janet Leigh who plays Marion
steals the money from the bank
that she works at
and she's driving off in the car
with forty thousand dollars in
the backseat, three hundred
thousand dollars in today's
dollars,
she stole the money, anybody
remember why she stole the
money?
Help repay her lover debts. 
Okay so
she's driving and all of a
sudden she sees her boss
yes and this scene very very
powerful scene and in the movies
So I thought we’d watch it together.
Film: "Marion, what in the world, what are you
doing up here, course I'm glad
to see you
I always am,
what is it Marion?"
 
Sosulski: So hopefully that jogged your
memory for those if you've seen
the movie
and so working working together
with Larry Engel the professor at
Columbia that I mentioned we
were you know trying to slow
down the film so what we did was
analyze this whole this scene
shot by shot in this process was
was somewhat telling give some
insight so kind of those things
that might add to the suspense
of the film so I slowed it down
shot by shot you see Marion and
you see what she's looking at
using their and this only told
so much
I needed more data
and so what I did is I analyzed
each shot
for specific elements that spoke
to the structure of the shot
itself not the narrative the
structure.
For instance
number of shots in the scene
there were nine
the length of the shot in seconds
and then the shot type
now shot type had to actually
create something called a
categorical variable right are
described the medium close up as
Giving it a value of twenty
just showing the proximity of
the camera to the subject is
keeping closer versus a full
shot which would be pulling out
or further away
with me so far?
Then, I visualize this
so I was able to see the
white line shows me the shot
length,
we know there's nine shots in
the scene already
First shot being longer last
Shot being longer like maybe some
shorter shots in the middle. And up top
is the shot type which I just described
to the proximity of the camera
to the subject
So what does this reveal? Let's go back
to the film.
first shot
We’re going to call that a medium close up
second shot Marian's point of
view the camera pulls out a
little bit
third shot back to medium close
up on Marion
Fourth shot what she sees you see the
same thing alteration happening
Marion what she sees, Marion what
she sees we continue on
until we reach the point at
which the boss has that point of
recognition
and then there's a close up on
Marion to build that suspense
and that that music that I won’t
try to imitate, that Psycho music
and in the scene and then get on
her boss and seeing Marion
drive away and so for me this
being able to visualize film or
visualize art
that was it for me
and I've been visualization has
been part of of my practice in
what I do to communicate through my
teaching but also anytime we
work we work with data to
communicate a message an insight
and so forth so what this can
also show is really the
deliberate
decisions that Alfred Hitchcock
made in designing this film in
some being able to see that
together
and stripping away
the visual content and looking
at it
in this way.
We showed this to students at
Columbia University
as part of a research study and
they were able to identify
different patterns of different
directors on how they construct
scenes just an amazing
experience for me and I wanted to
share it with you
so
Todd: This is the first time I saw
this too it was so fascinating
especially since that combines
the arts with that data which I
think your book does a lot
but this is your third book your
first two were on course online
course design you teach this
undergrad and grad students why
turn it into a book? Sosulski: Oh my
goodness well
how many students are in the
audience former students of mine
I really have to give
all the credit to my students
you've challenged me to build
the business case for why data
visualization is important to
managers not just you know a
skill that you're going to get
give an intern to do this is
something that is really so
important for management and
leadership to communicate
anything from you know
productivity to predictions.
Todd: That's great and Jim, a mutual
friend of actually is of friend
in the audience to
uses and references your first
book online course design all
the time for his work in online
course design. Do you see this as
a tool it and how do you see
people using the book?
Sosulski: That's a that's a great question
so I designed the tool the the
tool the book to be a reference
really so there's there's a
great chapter on design that
provides you with a checklist so
if you really know how to build
visualizations and you just want
to kind of refine them there's a
checklist that you can use or
something that you can use to
mentor others I have a series of
what I call architypes they’re
really like chart templates that
that's in the last chapter that
will just give you kind of a
head start on you know to build
you know the nine basic charts
to maximize readability and
clarity.
Todd: In talking about the chapters
that what other chapters can
readers expect from the book?
Sosulski: Okay so the the first chapter
it's called becoming visual and
that chapter is
really where I'm trying to
persuade my readers to build the
visualization as part of your
practice. I see it as the extra
twenty percent of anything
anytime you're working with data
the extra twenty percent that we
want to put in to make sure that
that insight that finding all
that great research and analysis
that you've done really shines
through and so building that into
your practice is it is quite
quite important so that's the
the first chapter
the second chapter but everybody
wants to know if the tools right
what's the what's the best tool
to visualize data and you know
they're going to change so I do
introduce you to several types
of productivity tools we call
those like Microsoft excel or
Google charts things that
we might use in our everyday
business practice and then
there's other tools that are
specialized visualization tools
like Tableau for instance or
ArcGIS if you're doing any kind
of geospatial
visualizations
and then I provide
a framework for how to evaluate
the best tool for your for your
task but also for the you know
if you're the one leading up
analytics and visualization in your
company which tools do you choose and so I
have a checklist that helps you
think about well the interactabilities
the sharing
capabilities all these different
kinds of questions you should be
asking so that's the first
couple there should
Todd: One thing that I thought was
really interesting when we were
talking and the video kinda
illustrates its data
visualization is really bringing
together design and data science
together which if you're you
know a data scientists maybe the
design portion can be a little
intimidating or designer maybe
the data side but you address
that in the book too right? Sosulski: So for
for none data folks there's a
chapter on data so how to
structure data for different
types of charts and there's
there's a whole section on 
data integrity making sure that
you know what your data means in
the real world sometimes we
throw these things into the
software and the output we’re
like we believe it and so kind
of developing that as part of
your practice and then there's a
chapter four for data
scientist that might not have
been trained in design to really
guide you in these different
design principles that are
influenced by you know folks
like Edward Tufte and and Amanda Cox,
and Diana Wong and and many
others Todd: Yeah it sounds like real
real tips for real people to
bring it to life and out one
thing when we were talking a
couple years ago I know you
spent a lot of time thinking
about because the words becoming
visual and it's in the title
of your book it's your website
hashtag can you tell us why you
selected
use those words specifically?
Sosulski: Yeah absolutely so it's very
deliberate
by selecting the the word
becoming
rather than be visual to suggest
that
you know we're all you know
visual beings and have designed
things before and so we're not
starting at zero and so that
that
becoming suggests that there is
there some past history some
prior knowledge that you have
about about visualization and
and data graphics and that that
is going to be developing
whether in the present and
maybe into the future.
Todd: That's great I love that
and one thing that you had
written in a recent article and
change this is okay I you
referenced a Marshall McLuhan's
the medium is the message and
apply that to data visualization
and can you elaborate for
those in the room today?
Sosulski: Yeah so there's a famous book by
Marshall McLuhan called
Understanding Media from
nineteen sixty four an oldie but
goodie and
I've been really influenced by
you know a lot of communication
theory and this this famous quote
the medium in this is the
message suggests that it's not
necessarily the content of the
message but it's actually the
form
the media or the medium that has
the ability to possibly change
The pace or scale of our everyday
behaviors so that’s the theory part of
but the
and how we apply that to you
know data graphics if you think
of data graphics as a medium
and you know it's it's the way
in which we expect to consume
data these days think about it
and pick up the newspaper it's
not like we're gonna see a you
know a big spreadsheet and so we
watch a tennis match you know
the the serve percentages are
Are visualized right right in
front of you and so
you know this is the interesting
way to kind of talk about
visualization as as a medium and
and think about how it changes
the scale at which we can
consume data and information in
today's data driven world.
Todd: In speaking about like the
different types of mediums and
you pointed this out before it's
like the difference between
designing a data visualization
for an iPad versus the power
point
can you talk to us about the
different I guess keeping the
medium in mind when you’re designing.
Sosulski: Yeah so format matters so if
there's any you know web
designers in the audience you
probably done a lot of cross
platform testing of of your
websites and things like that
but for you kind of have to do
the same thing for your visuals
so what I mean by that is when
you design something for the
screen to be projected make sure
that it's readable as me much
different in terms of how you
showcase that data visualization
you might not show all the data
at once you might deliver it
with a progressive reveal show
one data point at a time to
think about your role in showing
that data graphic so that's for
when you give live presentations
think about what is on an iPad
or for the web data graphics we
we want them to be interactive
we've all seen like the the
amazing graphics from New York
Times being able to kind of
develop your own story put in
your zip code or you know some
aspect of of of
that's that's personal to you
that the data graphic allows
their results to show you know
what what's the median income in
in in household income in my
neighborhood or in my census
track so those types of things
you have to think about how the
user is going to interact with
it imagine if it's for print
what kind of narration will be
provided or descriptions
Todd: And I love what you said at the
beginning about going the extra
twenty percent and that in the
storytelling element it can really
help illustrate a story better
and I can you share a little bit
more about what that means and
that in this context? Sosulski: Absolutely
so I have a joke in my class
like it's great to highlight
things in your data graphics so
say just think about a line
graph but you don’t want to highlight
everything because then nothing
stands out and so the careful
use of color the careful use of
what you show we might have all
the data I could probably show mapped
out you know all of Psycho for
you that might have been a
little bit too overwhelming you
know for for a three minute
presentation right so think about the
the amount of data that you show
and the level of knowledge of
prior knowledge of your audience
you want to be able to connect
with them and don't be afraid to
use interaction just because
you're using data graphics
another thought that comes to
mind is if you're gonna show
what you need to explain it
so a lot of times and we've all
seen this somebody just kind of
cuts and pastes something that they
found
on someone else's website a nice
little chart that might
illustrate an important aspect but
it's never spoken to
so that's always something to
consider. Todd: Oh and I love one thing I
have going back to psycho
is it not only can it help tell
the story but it could actually
help people look at things
differently too, can you share
some more examples of that?
Sosulsky: Certainly I mean being able to
see
for instance seasonal trends
so if I'm just looking at what
happened today which might be a
single number of my sales are
being I will put that in context
and see that you know there's
there's a similar pattern that
takes place you know every
December or something like that is one
Example. Todd: And I think as an even
where people can ask questions
about the data and finding what
X.
and the relationships of Y,
what are some of the questions
that people ask when they're
looking at the data?
Sosulski: Great great so
in one that I just covered but
what's
what's changed
right since from today from a
year ago from five years ago
What’s similar what’s different
so comparisons to contrast and
and contrasting items what
proportion of of something makes
up the whole
so if we’re looking at
other things are you know how
how close a proximity is acts to
why for thinking about locations
whether we're looking at like
you know
city bike rentals or really and
locations and their usage and
their productivity
or if we’re looking at like the
running paths of people who you
know run using a Nike app
kind of seeing those different
pathways that they may take
traverse though a city.
Todd: You recently did an
interview on a podcast about the
book and you reference one of
your favorite case studies which
is also in the book I which was
really interesting and I can
share that with us today?
Sosulski: So the author of that case
study he's actually in the audience
so so my former student and a
major contributor to the book
Andrew Hamlet did this amazing
case study where he uses Twitter
data to see if he could predict
the outcome of the two thousand
sixteen presidential election
and I think he was right
Which made the case study so
amazing and he visualized
he came up with a you know
entire rubric and quantified
various actions that people take
on Twitter like you know
mentions and re tweets and all
of this and looked at the
presidential candidates is able
to kind of show who is leading
at different points based on on
the metrics that he came up with
so that's my favorite case study,
check out chapter eight.
Todd: And I guess to your point
earlier they are for sale Iater
And Kristen will be doing signatures.
I love that case study because it’s
future looking and where do you
see the future of data
visualization going?
Sosulski: I mean just if you just think
about
how everything technology is
becoming so much more responsive
and how you know we can kind of
like control like the
temperature of our house
remotely and all these things
they were seeing metrics about ourselves
our spaces around us that were
visualizations are really you
know I hope one day it'll be
like you know a master dashboard
I can see my whole life in front of it
but I mean there's there's of
course us some danger to that but
I I really see the future is
being
visualization really becoming
the interface for how we
interact with you know spaces and
places.
Todd: I think that goes back to that
words becoming visual to that
were all
becoming visual and speaks to
that a lot
how
one of the things I know we've
got Q and A and then some
networking afterwards, and one
thing that you mentioned in the
book is a party favor and you
apply that principles
to data visualization can you
tell us what you what you mean
by party favor in the book? Sosulski: Yeah
yeah so chapter nine where I
kind of leave you with some
archetypes or templates for you
know building your own data graphics
there's also like a few what I
call cognitive short cuts and
one of them is the party favor
or you can call it the
wedding favor so you know when
you leave a wedding you always get
like a nice little trinket to
remember the day well think
about that every time you create
a data graphic what's the take
away what do you want your
audience to leave with and so a
quick way to remember that is
that the party favor.
Todd: And one thing I didn't realize
until we were prepping for
this is that there's thirty
different types of charts
and I I guess the podcast said
that there's a
some people don't like pie
charts
I don't know but do you have a
favorite chart and can you tell us a
little bit more about how how
you decide to use which
chart for what. Sosulski: That's that's
a great question so and there's
a really simple answer it all
depends on your data
so if you don't have location
like latitude or longitude or
zip code guess what no maps
right you can't you can't use
the map
So that’s obvious if you don't have
time series data like an element
of time
no line charts sorry
so your data really does
dictate the category of charts
that you can choose from so if
we're talking about times series
you know there might might
only be like 10 to choose from for
instance and you know I'm always
a fan of like the geospatial
displays because I just think
it's so great to kind of visual
visualize a space around us so
those are those that I tend
to gravitate towards. Todd: And I
think on the podcast you actually
said that we as humans actually
are able to
digest length better than than a
pie chart is that right?
Sosulski: Yeah so there's there's there's
been research that probably many
of you have heard of about
That as humans that we can discern
and detect length better than
we can of area so like a wedge
of a pie like how big is this
one verses this one versus the
length of a bar so if you're
showing ranking in terms of like
you know who has the highest
score on a test out of like thirty
students it's see like a nice
long bar and you see that person
like their forty so
it's very easy to see and detect that type of pattern
insight like min’s and max's and
and minimum values and maximum
values pretty easily with with
bars lot harder when we're
looking at proportions in 
a pie. Todd: Yeah I thought that was so
interesting and it's in the book
you also as you mentioned Tufte
And you mentioned thirty
different charts and you
mentioned The New York Times are
there any data visualizations
that you think are the most
beautiful or is like The New
York Times a great example of
really pushing the envelope for
using data visualization today?
Sosulski: Well I I'm like I'm the biggest
fan of Amanda Cox from the New York Times, so
anything that she does I think
is amazing and
you know and she does add a lot
of like beauty and aesthetic
elements to her charts
which I love she has one about
how people spend their time
which I think is great and you
can look at for instance you can
compare how like unemployed
versus employed people spend
their time and it was the the
stacked chart one hundred percent stacked
area chart if you want to know
the technicalities but you'll
see that people that aren't
working how much more time to
spend on movies and TV so
there's like funny and fun
insights it's also interactive
so I could I could choose you
know like all my attributes
employed female blah blah and
see how people like me spend
their time.
Todd: that's fascinating
And what it
what is that you mention Tufte and
what are some of the other I
guess thought leaders in the
field that have shaped your work
or that you mention in the book?
Sosulski: So I mentioned already Amanda Cox,
David McCandless and
Lee Byron they’re really big in
the in the field of
visualization on they have a
famous Ted talk which is one of
my I think you've seen at one of
my favorite graphics
and so that them also
this woman who works at the
Fed right now Donna Wong she's
done some amazing work it
actually was an assigned
textbook for for my students
about how to communicate like
financial data like really
really clearly and and how to
build your own metrics that you
can visualize to not just take
the data how it is but actually
you know build in your own
percentage change or something
like that as your own metric so
these are these are some of my
influences for sure. Todd: That's
Great, you mentioned the one
case study, what are some of the
other ones because 
students did help contribute
more to the book too right? Sosulski: Yeah
so there aside from case studies
is actually interviews so there
is an interview from a former
student on how she use
visualization for her age HR
consulting practice
there are this visualization
around how
you look at the pathway to
conversion for a product so by
device type so maybe you're on
your phone and you start
browsing and you like something
in Amazon and you put in your
shopping cart but when do you
actually convert you convert
when you get home on your on
your laptop? Do you convert on your
tablet and you're like in bed
reading like what what I what
point does that happen so that's
really an interesting
visualization that you'll see in
a very sophisticated in chapter
two so those are just some
examples. Todd: So who would read your
book I mean you mention students
but also MBAs.
Sosulski: I hope everyone
you know my goal is really just
to make it accessible accessible
to anyone from you know
designers to data wonks is
kind of my tagline
but really anyone who is
interested in using data to tell
stories or
have an alternative means for
exploring data visually so
that gives an access
point you don't to be a data
scientist to visualize data and
I think visualization gives an
access point to really working
with data if it's something
that's new to you.
Todd: Can I read a a line from your
Manifesto?
I really recommend this
article that she did in
change this:
“Ultimately the way information
is consumed by the audience and
their impact on our
understanding of the world is on
the shoulders of the creator and
the medium they choose to convey
It” so no pressure for anyone on data visualization. So what
does this mean to you in the
context of today and all of the
data visualization that's out
there?
Sosulski: Look like if you're building it
you're completely in charge of
what you show
so if you decide to show only
part of the story you know
Show time series from you know
two thousand sixteen on what
happened in two thousand fifteen
you chose to omit that data from
your visualization so it's
really how you show it what
you're showing and then how you
show it to you or you decide to
show it where you show it all at
once or you kind of tell a story
with it and show point by point
so that's another thing so
you're kind of in complete
control of the message in the
delivery of it if you're
building it
Todd: And I actually
hear you speak at the New York
Times' offices to a group of
industry professionals and I
believe you're also known for
taking photos of examples
in the media of
data visualizations gone wrong
can we say?
What are some common mistakes
that you see? Sosulski: Just like
over exaggeration of the data
graphics to represent the data
and so what I mean by that is
maybe there's like you know a
one percent change and the
exaggeration shown in the
graphic shows a four hundred
percent change to kind of make a
point or statement but it's it's
really it's really lying with
data
so I've seen that quite often I
had a fun collection
I should do it Instagram on it.
Todd: Or we'll save that for another
another presentation
well we've got about ten minutes
left and then we're going to be
opening it up to audience Q.
And A so definitely get your
questions ready
so I guess that one thing that
I find really fascinating is one
the combination of your
love for the arts and then for
data science and learning
and how you bring you merge all
of that together and when you
are thinking about data
visualization and your students
and having a message received
like how how do these worlds
collide for you when it comes to
learning your learning science
and data visualization?
Sosulski: That's really
something I thought about a lot
I don't and I'm still working on
my answer so I'm I'm I'm
developing it at but
I really see
visualization as a way to
provide evidence so if I make a
claim I want to show you what
that means using data to support
whatever it is that
that I'm showing and so
for it for those of you in grad
school you know like cite your
sources right and so it's it's
the same type of thing
to be able to provide evidence
for why a particular
phenomena or trend is happening
and to be able to not to say it
but to show it and that's always
been like a big part of my
practice I always and for
students in here you know most
of my class you're you're
working I try not to talk all
that much and the idea is that
to be able to
to learn by doing and I I
that's where it kind of that
title becoming visual came into
so that that it's a practice
And it the process so it's
something for you to do not just
kind of observe.
Todd: One thing that you had
mentioned when we are talking
prior to this is to let also let
people know that they're not
alone and to talk to people and
the need to get out of your
bubbles when you're talking
about data too.
Sosulski: Yeah one thing that is absolutely
mandatory like all the work that
that I do for myself
my rule is show your work to
others and don't be afraid to
it's really hard
it's really really off a
difficult thing to do would be
able to should be open yourself
up and allow that critique to happen
it'll only make you better and
people generally be excited
about you know providing that
that feedback and so that's
when you create a data
graphic for instance be tied
back to that show someone else
if they have the same
interpretation if they have a
different one that might be
something to worry about
Todd: Better to do it before you put
it on Twitter
yeah well and one thing that I I
mean I learned from you, well I
learn every time we connect is
actually mastery and since we're
at NYU
I thought it would be interesting
to ask a question like how does
one become a master of data
visualization? Sosulski: Gosh
I mean the research that I've
read about how people develop
expertise
it just takes it takes a really
long time and it takes about
like at least like ten years
like full time to be an expert
in anything in these days we
think because we did a
tutorial we have this over
confidence that we can kind of
just do it we usually can
being highly productive people
of course but so it it's it's it
just take it really does take
you know building things in and
developing a practice and having
that open mindedness being able
to have the language to critique
and also to be critiqued.
Todd: Great at let me do a time check
we have just a couple more
minutes until questions so get
your questions ready I guess
You know you set out to make a book
as a tool open to everyone you
know what is your party favor
that you want people to go home
with like what you're one take
away about either your book or
data visualization that you want
the audience to to leave with?
Sosulski: Great so that you're that you're
ultimately you know the work
that you do you’re ultimately
designing for someone else and
so you know just just be really
thoughtful and all these things
are about being thoughtful and
those things you create and you
share because you're ultimately
want people to understand your
message and walk away not being
tricked or confused or stumped
but really really having that
that insight that key insight that
Message.
Todd: And who would've thought it
started with Psycho
well thank you so much 
this has been an honor, why
don't we open up to the
questions on the floor so I'm
not the only one asking
questions
do we have any I guess we're
just raising
Hands, Callie
the master here we have someone
up here with it raised hands and
I think a Mike will be coming to
you in just a second
Audience: Kristen do you have any point
of view on the future of three
at three three D
data visualization particularly
for use by data scientists in
large corporate environments?
Sosulski: In this innovation lab
that I work at at at Stern
there's been a a few startups
working out space doing some
visualization that's that's been
in 3D.
And I mean I wore like the goggles
and and everything and I think
it's about how how that gets to
being interpretable by a lay
audience right now I I find I
find there's a complexity needed
but for analysis I see huge
potential
yeah that's a great question
Audience: Hi Kristin you you mentioned
you mentioned a
tableau I'm interested to know
which applications you use most
for your visualizations I've
spent some time with click sense
and it's been quite well have you
used that one as well?
Sosulski: I haven't, no no
I've used Tableau, I use
Excel and I also use R, so do a
lot
of visualization with R and
creating interactive shiny apps
things like that in addition to
Tableau that's usually my tool
kit if I'm doing anything
complicated geospatial I'd go
ArcGIS for something simple like
even the Psycho I might use
today I used Keynote because
it's really simple and a lot of
a lot
of the design elements already
in place for me I don't have to
remove a lot of that chart junk,
there's grid lines, tick marks
and all that stuff that
really are those non data
elements. Audience: And R is just the
letter R?
Sosulski: Oh,
so R is a statistical
programming
environment yeah yeah yeah so
you could also do visualization
and in Python but
R is really designed for
working in data at the core so it
has a great number of packages
for visualization. Audience: got it thank
you
Todd: I guess one question if there's
anymore as where can people find
you online and get the book yeah
we could do a plug for your
newsletter
Sosulski: Sure so
you can obviously you can get
the book on Amazon and go
directly to the publisher website
Routledge I encourage you to
to do that
there's a site called becoming
visual dot com and it's really
for anyone in the world there
are tons of tutorials and
resources it also has the
accompanying resources that that go
along with the books so you can
try out the exercise on your own
you can download the data all
that good stuff so becoming
visual dot com and you can
follow me on Twitter and that's
usually where I post most of my
my updates and then you'll get
redirected from there.
Todd: You mentioned a course a
new certificate at NYU do you want to
share about that? Sosulski: So this is
how all my worlds emerge
so I'm offering an online
certificate in visualizing data
and it's going to be from
February fourth to March thirty
first still be completely online
and it's based on the book but
it's it's again it's good it and
even think of it the book as you
know becoming visual on this is
the practice of becoming visual
is really with the course is all
about.
Todd: we have a few more questions Audience: Yeah I 
have a question all the way in
the back
you kind of alluded to this in
terms of you're saying certain
data types are more conducive to
certain types of visualizations
and a person's question up
before about 3 D.
you're saying that it's hard to
interpret I just wonder if there
are any sort of common
misinterpretations of certain
types of visualizations similar
to certain like linguistic
common misinterpretations or
quantitative common
misinterpretations just to know
so that if you're presenting data
To an audience that you
if you don't intend to miss like
what you're saying with
exaggeration example you don't
intend to
like confuse them you you you do
because of this common
Misinterpretation.
Sosulski: Yeah I'm gonna go back to my
response of like sharing that
with others so pilot test it beforehand
to kind of anticipate
those common misconceptions you
know whether talking about like
linguistic visualizations right
so you need to have like a deep
knowledge probably of of of that
field or or what those
visualizations and relationship
in between words so I I would
really start there.
Todd: Do you have a mike already?
Mike is on the way
Audience: Hi I have a question how do you
think artificial intelligence is
going to change or reshape data
visualization?
Sosulski: That's really really interesting
the analytics from it for sure
tell me what's happening behind
the scenes at a absolutely what
I would want to know and be able
to visualize in terms of
artificial intelligence what's
the interaction between the user
and the machine and how can we
have a we see that behind the
scenes
for not just one but you know
millions of people I think that
could be really really amazing I
want to be able to do that with
you know even how people
traverse you know online courses
and things like that those
things are really interesting
and there's a whole area of
learning analytics so I imagine
that with artificial
intelligence is there's a huge
Opportunity.
Todd: And you still need good data going
As an input too right?
Sosulski: Absolutely and that's that's the
problem with a lot of these
these systems today is the inter
operability between between the
data and and the systems and so
getting in the right form being
able to visualize it tends to be
a big barrier to even beginning
yeah it's a good point
Todd: We have another one. Audience: I was really
intrigued with how you started
with Hitchcock on analyzing the
video given how video is
becoming ever trendier
especially in the online
landscape I'm wondering if your
research has included applying
data visualization techniques to
that format whether you think
that's a positive way of moving
forward or if an interactive is
more useful or any thoughts and
that sort of problem.
Sosulski: gosh I love to spend more time
on that yes
I have I have I have thought
about that and I think the
possibilities of of being able
to automate some of this put
some of these processes it's
really exciting like what I
showed you is the project from
2002  that I did by
hand right so I think having
that I think could really
open open the door to new
possibilities and using this
kind of process even to look at
anything not just film but if
you're looking at like
commercials and and and and and
in this type of way it could be
really interesting.
Todd: I think we have time for two
more and I think someone okay to
more hands raised which is
perfect.
Audience: Hi of what do you find that
students have the most
difficulty with in the course
say you're teaching this data
Visualization?
Sosulski: My god they’re amazing nothing
well that's a that's a very very
good question I think it's about
the the rigor of putting that
extra twenty percent in on
refining the graphics it takes
time and the reward isn’t there
until you show it to somebody
and so we're doing the homework
and the work they reward us is
there isn't there except maybe
the grade or something like that
Intel you're actually using it
in real life and so that bridge
from you know theory to practice.
Todd: And I think one more question it
here and this will be our last
question
Audience: So you mentioned like trying to
tell the story about your
visualizations I was wondering
prior to knowing what the story
is if there's a different
mindset in terms of doing a
discovery process of different
techniques around around that?
Sosulski: Yeah absolutely I see
visualization as having you know
a dual role one for data
exploration the other one for data
presentation and they're they're
different and usually you're
doing the data exploration
anyway and so well it could
be very easy to run summary
stats sometimes visualizing the
summary stats to kind of see the
presence of outliars for
instance is a very important
task.
Todd: Are the books here
okay this is this is
well thank you so much for being
here and for sharing your time
with us today and let's all just
give a round of applause to
congratulate
Sosulski: Thank you so much Helen this was a great conversation
thank you Phil for a wonderful
introduction and and your
support and to Callie Short
who like arranged this whole thing
amazing so thank you.
Nuzhdin: Thanks again Kristen and Helen for
an engaging and thought
provoking discussion I know from
personal experience I work in a
investment banking and recently had a
training course on presentations
and best practices and they
basically told us listen if you
have nothing new to present
which happens very often
Present it differently so definitely
Relevant to the real world experience
I want to say thank you to every
everyone each of you in the
audience for coming this evening
to further your lifelong
learning and to hear from
Kristen and Helen as you’ve already heard
Kristen
offering an entire on line
certificate for certificate
course in visualizing data beginning
in February this course will be
open to alumni and is geared
toward those who want to
improve data
visualization best practices and
as a closing note I
wanted to say your engagement
with NYU Stern enriches
Our vibrant alumni
community and I encourage each
each and everyone of you to
continue attending these of
events and those in the future
including the upcoming Fintech
conference I believe there's
fliers available in the back of
the room for that as well
supporting stern's fundraising
initiatives I know many of you
already donate both your time
and resources to many
initiatives at the school and
for that we thank you a lot it's
definitely meaningful it's very
impactful for those of you who
are looking to be more engaged
and more involved there are many
opportunities available for you
to participate and stay engaged
one these opportunities I want to
Speak to today is continued giving
it's a benchmark that not only
allows us to retain our
reputation within NYU and
competing business schools out
throughout the country but also
provides opportunities for
scholarship to needy to
underprivileged students as well
as funding world class research
so if you haven't given recently
and I welcome to do so through
either an online appeal or
through one of the envelopes
available in in the back of the
room and with that we will now
move on to the cocktail portion
of this evening we're Kristen has
graciously agreed
to sign books,
hopefully there will be copies
available
for purchase towards the back of
the room, and finally I want to
say the final thanks Kristen and
Helen, thank you for being
here
with us this evening and please
accept this as a token of our
appreciation.
Thank you.
