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okay let's get started
so as far back as two thousand
ten M. I. T. in
the study they did with IBM
talked to more than three
thousand business
executives they asked where
are managers who deal
with data headed
and as you see they predicted
that even within a couple years at that point in
time data visualization is going to be
the analytic technique that
creates the most value
for organizations
and it has only grown
since then
so we continue
Gartner back in two thousand fourteen
developing a magic quadrant
on business intelligence data
analytics and they talked
about how it's going to make a hard types of
analysis easy
and easy for an
increasing set of
users those with a little less
technical knowledge maybe but who
understand data and
some of the implications in the domain
areas that the data is going to be used
so this is where that
whole market is headed and now we see it
being used just about everywhere you could
actually get data
visualization classes at
university whole classes on data
visualization designs of
data visualizations and so forth
so you'll see it as all whole class in a full
blown business analytics program
and we're seeing this even
out at the corporate level with
companies starting to actually
list positions for data
visualization experts
visual storytellers and so forth
so here're a couple that I was just able
to pull up by doing a search
on indeed dot com data analyst
reporting data visualization and Disney streaming
services thermo Fisher
scientific even a data
visualization manager at
Deloitte
so this brings to mind W. Edwards
Deming who was a business
consultant back in the
nineteen fifties who
really revolutionized the
manufacturing process he
actually pitched his processes to
US companies after World War two by
that point in time they were kind of the leading
economic engine on the planet and they said
no thanks so he brought his ideas
over to Japan and slowly
but surely Japan got better and better
doing things anyway one of his
quotes is in god we
trust all others bring data
is Japan ended up moving
toward what we now know as the T. Q. M.
method total quality management
approach to
manufacturing and organizational
processes
so what we do with all that data well
that's where data visualization
comes in and why it
seems to be more and more
important every day so let's
take a look at a grid of
numbers and let's see if we can figure
out how many times does the
number seven appear in
here
so one thing about this
review is it does take a good bit of
time to find all those sevens
and you'll probably find if you do this
with your friends that you come up
with different numbers
just depending on how much time you spend
with it how thorough you are how well
your brain processes numbers all those
things
now now how many sevens are
there
so we made one
simple change we change the
color of the sevens
now it's a lot easier to find them so our only
task now is to count them
and make sure we don't count the same one twice
what about if we bold it  so that adds a little bit more
even
we could underline them
so each step along the
way we're doing something that makes it
easier for that seven to jump out at
us these are called
preattentive attributes so we can do
all kinds of things to those sevens we can
change the color bold them italicize them
underline them or even add a drop
shadow like you see down there at the bottom
so color size
orientation and texture especially if you're
using black and white only
publications texture can become important
there so these are things are called
preattentive our brain
can process these preattentive
attributes in two hundred fifty
milliseconds so
these happen before we would start
thinking about what it is we're looking at
on the left we see some of those preattentive attributes
now the other thing that we process
without thinking about very much is
color so we can
encode color lots of different ways we
can use shading etcetera
and again our brain can process
those color differences and notice them
quickly before we even start thinking
and depending on what we
wanna do we may choose
the best preattentive attribute to focus
on some are better for precise
quantitative comparisons
length and width give us a common
baseline in two dimensional
space if people are standing right next
to each other we can easily see which one's
taller which bar is longer
than the other one or taller than the other one
etcetera but if they're far
apart it's not so
easy and here are ways we can use
position as a preattentive attribute
order also is very powerful we
could just rearrange all the numbers make sure all
the sevens are up top here we can
see we have one full row of
sevens so we now are starting to
develop a little bit more information
about this data than we had
before we're starting to turn this
data into some level of information
here we didn't even do anything to the sevens
but we grayed everything out a little bit in the
background we made it a little bit lighter so those
sevens jump out at us even more
than they did before now if we want to highlight a
different number at this point we can make the
fives a different color
make them black or
red or something like
that
so if we have black text that we're
working with and it's already bolded well we can't make
it darker or bolder
so a lot of our data visualization
tools tableau is probably
one of the forerunners there
realize this and they give us kind of a light
gray type face as a starting
point for just about everything it does
so the number of times it did appear
is seventeen so we could put that in a bar
chart along with the other digits and
see how it looks so we now have a
little bit more information about not only the
sevens but the other numbers as well
now we can also order them right now we have them
ordered by the number of the digit
we could order them by frequencies so we can
see here seven comes up
about the same number of times as one
so here if I were just looking at the bars
without the labels at the end of
them I'd say yeah looks
like seven came up about the same number of times as four and
one and they are the two closest
now easily find well what was my most
common number what was my third most common
number that might be a little tougher to do
here so just depending on what you're trying to
do you may order these differently all
right so let's take
a look these pie charts so pie
charts are problematic in a number of
ways how would we answer the same
questions which digit showed up most
well I see a blue slice that's thirty
four is that three the same
shade or is that one the same shade over on
the legend here on the right
you see you kind of have an awkward
wheel of
legend indicators
around the perimeter of that
pie so I guess
the digit zero showed
up ten times etcetera
all right so you know work a lot
harder to figure out the
answer to any questions you have with either of these
approaches than you do right here
or even right there
so the idea is we want to
move from data to
information how many
how much we want to move
into the why questions how can
we do something going forward how do
we decrease expenses how
can we how did we
all right so data visualization is
terrific for how that works
but the human beings
and we're always communicating with human beings
need to be able to interpret that
appropriately
so let's take a look at some other
aspects of visual perception
you'll notice often even when we're
discussing things with no
visual support
people say ah I see
or show me
so we refer to our visual
sense frequently
so this image
is an object that appears to be gray on the
top white on the bottom
now you might be surprised if I told you that
the main shade on that
top piece is the exact same
shade as on the bottom piece
let's check that out
the reason is that we
perceive light to
come from above so
we assume that the sun is
shining on that darker gray
and lighting it up a little bit but that the
white lower portion is in the
shadows so that's just a
natural effect of the lighting source
okay
so no real shadow this is a two
dimensional image
so we pull back out
and see that is the exact same shade all the
way down all right so same
thing here now this worked a
little bit better back in the days
before we had higher
color accuracy in our
computer screens so how many shades do we have
here
and depending on how well you
discern color you may say
two I've got the light blue on the left
I've got the dark blue on the right so I guess
the qualifier there would be
how many shades of blue you see
and depending on how well you see
color many people will likely say ah we've got
two we've got the light blue on the left we got the dark blue
on the right
now if we move things out of the
way we could see we actually have
four distinct shades of
blue
all right so let's take a look at this
young man standing in the corner of a
room
and now he's on the other side of the room
wait a minute what happened did the boy
grow
did the room shrink so
what's going on here
if you've ever been to one of those funny
house tourist trap type
attractions you
probably realize that the room is
actually not a standard
rectangular room but it is much
deeper here much farther back to that
corner but it's set up in such a way that when
we view it from this particular
angle it has
a square look to it so that we
see it as a regular room
and the kid is just getting bigger and
smaller
all right and this is kind of the same
concept as you have here
where you can fit the Washington
Monument between your fingers there used to be
a show Kids in the Hall where they
would do that with people's heads this
picture actually reminds me of a friend of mine
who always would take a picture of
his wife with some kind of monument
or landmark coming out the top of her
head in the photo so
here's to you Dave
here's how they set up their room
just like we see now in this case it would have been the
angle on the other side of the deeper angle
on the other side but if we're looking
from that one end of the
room here's how it works and the
name of it is an Ames room
all right another way we perceive
distance so let's take a look at that blue
line further down the railroad tracks so you
might think that that's a
longer line than the one in the front but if
we bring everything together you can see they're the
exact same distance
so the notion of perspective
comes into play here we sense that these
railroad tracks are getting farther away from us
again even though it's a two dimensional picture
and we do those mental gymnastics
in our head
all right so shadow also plays a
role in helping us determine three
dimensionality
so do these buttons seem
to be pushed in or
kind of indented in and which ones seem to be
indented out
most people would say
that light typically comes from above
so let's see
the top center and
bottom center ones we would think are coming out
and the other ones would be pushed
in indented and if we rotate
this all the way around then
even though it's the exact same image our
perception gets reversed
here's another one of a
crater black and white
or is it a crater
looks like it might be a hill that we have to
climb instead
so again perspective lighting
what we expect we kind of fill
in blanks
so here's one that is it can
be a little bit unsettling and we
call it the Moirￃﾩ effect so
when we've got all kinds of lines real close
together like this we might see some kind of a
shimmering effect when you look at
that image too intently
that's not a comfortable feeling for some of
us and it gives us some of us that
feeling at least in my case that's real
similar to when I try and read for an
extended time period in a moving car
and now if we stack two of them on top of
each other it gets even worse so think
about that when you decide how to
set up gridlines
on your bar charts or line charts look at
that top one there're so many grid lines that
you almost get that Moirￃﾩ effect
and the gridlines are dark y'know real
small increments and they get in the
way of us being able to actually read this
chart do we really need to know every fifty
or would something like
what we see down below work a little bit better
yeah we know they're getting better we're getting a little
over two hundred by seven
o'clock for the blue line all the way
up above eight hundred by the
end of the evening for the purple line
and we've grayed out those
gridlines so they don't create
quite so much visual clutter similar to
that effect we have with the gridlines if you have a
bar chart with just too many bars you get
kind of that same deal in this
case you might just want to eliminate the
spaces between the bars
in which case you would have put colors in
instead but when you
have this many you might want to rethink your
approach another effect is called the
Hermann effect or a scintillating
grid so what happens is
we move our eyes around and look at
different pieces of the grid
we see what look like
dark spots in the
white intersections of the
places were not looking directly at
so this is a little distracting
and something you might want to keep in mind if
you put together unit chart like this
again you might want to instead of
just having a big wide line just
make a hairline between your units
the Gestalt principal here again
we're filling in the blanks just like we did from a
perspective standpoint with the train
tracks receding away from us here we
fill in the blanks of a shape
that's implied by what we see here
we fill in the shape and see that triangle
and that white triangle on a white
table apparently is covering
three full circles right
well of course there's no triangle
there're no circles we just have those
three Pacman shapes but
our brain fills in the details for
us same thing here we're gonna fill in the
blanks we see the circle we see the
triangle we even see that rounded
rectangle outside surrounding
everything and here we can see what
looks like a jumble of pick up sticks
maybe maybe one's broken
and as we fill in letters
around we can turn it into
whatever we need going from left to right
we'll turn that into an "A" cat
sure going top to bottom
we'll turn that into an H. the word
THE
proximity also plays a role that's
another Gestalt principal where we fill in
details based on proximity so
if we're encoding our squares with different
colors our brain groups them together for us
automatically so if we were to
say are there more blue squares
more black squares more orange squares
our brain sees all the blue squares lumped
together so most of us would just
immediately say blue
and as we can see we end up having the
same number of each
color
so again understanding how our mind
processes visual information can
help us design it appropriately
so we can use this
proximity anything that's near each other
is going to appear to belong
together we adjust the
space and all of a sudden we have four
small clusters or next to that we
have four rows of data
over to the right of that we have four
columns of data
next we have four columns of data in
the lower left but we're alternating
color rows so here were mixing colors
and rows and columns
of data and in the final one just by using
color we can create a square
inside that array of
dots again not a ton of
shifting just a little bit
shifting the position or shifting the
color or shifting both all right
so another thing is our brain
processes information all the
time but our brain
does like to work efficiently
so let's stare at that dot in the center for
just a few minutes while I chat
so our brain wants to conserve energy and
as you stare at this your brain starts to
say
yep it's still the same yep it's still the
same every few milliseconds
and it finally says okay I've got
it I don't have to keep processing
this same picture because I
know it's gonna be the same the next time I
refresh so much like a computer monitor
your eyes and your
optic nerve process visual
information at a certain speed
all right so we're still staring at the black
dot now I'm going to switch to the
next screen and just keep staring at that
same spot now is that picture in color
sure looks like it
but as you continue to look at it
you'll see it actually is not
this is a black and white photo
but by
superimposing that retained
image in your brain over the
black and white image it appears in
color and we can do that same thing here
okay so here we're looking at the lady's nose
and we'll do the same thing here but this
time the next screen is going to be
perfectly blank and we'll see what we see
and hopefully you were able at least for a few
seconds see that lady's image so the
idea is we've got all kinds of
data in our world the tools
help us look at what has happened
what's happening now what might
happen in the future we can test our
model different scenarios so the
main goal is to
understand our
world our business our
process a little bit
better
change our behavior make better
business decisions etcetera
and we ask our questions of the
data to do that so this is
a process of human
cognition asking those
questions finding patterns
or verifying patterns that our
tools have helped us discover drawing some
meaning
so this is a creative process
visually driven it requires
those empirical mathematical skills as well though
because the tools are bringing those to
our fingertips more and more it
absolutely requires subject matter
knowledge you need to know your industry you need
to know your business you need to know your
function so the software helps
us a lot but the computers
can't figure out what it means at this point in
time we're not there yet
how it connects to the problem what
we should do once we have that information
so data needs are changing we're
dealing with more and more different types of data
all the time and the
objective is we're all used to
smartphone interfaces now we want it to become
that easy to do just about anything it's
not that easy so knowing how to
work the tools to get the information
in a good display is a
difference maker for you
again we don't typically train for this visual
intelligence but it's something that you might
want to work on and practice with
to get better at all right last take
away
so of course almost any of us would look at
this and say yep this is a dashboard
it's a data visualization no doubt
about it
what about this
would we consider this a data
visualization
this is the website for the Cleveland museum of
art so the data is the pictures of
the art they have in the gallery all
right maybe not the kind of data you and I think about day in
and day out but
what if we do this let's say we've got it
set up so that when the user hovers
over that picture it gives a little
more information those of you
who've used Tableau are already familiar with
that now if we click on it
we bring up even more information
we've got the title of the piece we've
got some basic information
about it
maybe we can scroll down so certainly
I would hope you can now think of that
as a data visualization
remember we're trying to understand what's going
on
make better choices change our behavior
etcetera
understanding how
visualization plays a role is going to
help us get there hopefully for everyone
so that's it for our overview of
visualization and the human brain I
hope you found the video useful be sure to check out the other
videos available in this series
