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From YouTube: Eugenia presents Data Analyst Intern Project
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A
All
right
is
this:
gonna
ruin
see
yes,
okay,
all
right
so
hi
everyone.
This
is
my
intern
project
presentation.
Let's
get
started!
First
of
all,
hello
I
wanted
to
reintroduce
myself
today,
but
I
am
Eugenia
and
I
started
here
at
gitlab
as
an
intern
at
the
end
of
May,
but
my
internship
is
only
technically
30
days
long
as
I
was
doing
two
days
a
week
until
now.
So
that's
me.
A
Well,
I
had
the
opportunity
and
I
really
wanted
to
hashtag
Summer
of
Code
2019
I
was
given
the
chance
to
improve
my
skills
as
a
data.
Analyst
and
I
ran
with
it.
So
that
being
said,
here
is
a
brief
overview
of
what
we're
talking
about
today.
The
idea
working
with
the
data,
the
insights
that
I
gathered.
What's
next
like
what
could
be
next
with
the
project,
I
developed
a
inclusion,
okay.
So
to
start
with
the
idea,
I
was
thinking
about
what
I
could
do,
what
I
could
research?
A
A
Well,
the
onboarding
issue
right,
everyone
has
to
the
onboarding
issue:
I'm,
not
talking
about
team
specific
operating
issue.
The
people
of
onboarding
issue
has
days
one
through
five
task
completion.
You
everyone
does
this
right,
so
I
thought.
If
I
look
at
this
information,
there
must
be
a
way
that
I
can
look
at
open
or
higher
date.
Date
started
and
then
closed
date
and
just
kind
of
try
and
get
like
a
general
view
of
not
only
how
the
onboarding
issue
performed,
but
also
how
the
folks
doing
it
ideally
perform
within
the
unbury
issue.
A
This
was
probably
the
most
challenging
part
of
my
internship,
like
all
data
analysts
have
to
clean
their
data
set
and
I
was
faced
with
a
number
of
challenges.
I
had
never
encountered
before,
including
kind
of
string
parsing
in
sequel,
I
really
want
to
get
in
to
the
nitty
gritty
of
like
what.
If
you
know,
everything
I
had
to
do,
because
it
was
so
torturous
and
I
want
you
all
to
experience
that,
but
I'm
gonna
actually
not
do
that
to
you.
A
But
this
is
a
good
kind
of
personal
representation
of
what
I
was
doing
in
terms
of
cleaning.
So
yeah
working
with
the
data
primarily
was
me
getting
it
to
a
point
where
I
could
start
doing
analysis
on
it.
Okay,
now
I
am
going
to
show
you
my
work
in
progress.
Periscope
dashboards,
they're
gonna,
like
hop
out
of
this,
and
into
what
I
did
so
I
three
charts.
This
first
chart
being
the
cumulative
closed
issue
by
cohort
so
basically
I
broke
down.
A
A
A
But
then
on
the
fifth
day,
the
incomplete
kind
of
kind
of
jumps
up.
So
I'm
gonna
go
back
to
my
presentation
and
talk
about.
Nobody
gave
you
like
a
brief.
You
saw
what
I
did
a
little
bit
and
you
can
feel
free
to
check
it
out
and
look
at
it
further.
But
basically,
if
we
look
at
July
2018,
due
to
july
2019,
we've
had
109
percent
increase
in
burning
issues,
which
is
crazy,
but
also
fits
with
the
hiring
patterns.
A
Thank
you,
lab
is
on
and
the
average
time
from
higher
tuition
close
date
has
decreased
by
a
hundred
fifty
seven
percent.
So
that's
like
131
day
decrease.
So
that's
good.
That's
a
good
sign
and
tasks
by
day.
This
one
I
think
is
something
that
we
could
take
and
iterate
on
much
further
in
terms
of
getting
down
to
the
details
of
like
actual
like
what
actual
tasks
instead
of
like
just
letting
them
out
by
day.
A
You
know
splitting
if
we
can
figure
out
a
way
to
split
out
actual
like
each
task
and
then
see
if
there's
one
specific
task
that
like
people
are
not
doing
or
you
know,
and
then,
if
they're
overwhelming
a
number
of
people
not
doing
it,
you
should
just
get
rid
of
it.
Things
like
that,
like
using
more
of
a
drill-down
task
by
day
analysis
to
like
make
decisions
on
what
we
should
include
the
onboarding
issue
and
not
hey.
B
A
A
B
A
B
Said
no
yeah
I
was
gonna
say
that
one
cohort
chart
like
the
first
one
that
she
showed.
Maybe
there,
if
you
could
you
know
that
that
might
be
able
to
help
say
you
know
this
cohort
after
that.
You
know
those
mass
closings
of
issues.
Then
you
know
that
would
be
a
good
point
of
comparison.
A
A
C
A
A
You
know
just
to
kind
of
breaks
out
and
look
at
it
ways
that
we
can
in
the
future.
You
know
the
more
we
the
more
we
shape
the
onboarding
issue
that
everyone
has
to
complete.
The
more
specific
we
can
get
about
tracking,
that
only
performance
of
the
onboarding
issue
itself,
but
ultimately,
to
then
see
if
we
can
take
onboarding
issue,
performance
and
overtime,
look
at
individual
performance
and
see
if
there's
any
relationship
between
like.
B
A
So
yeah,
this
is
that's
basically
that's
my
periscope
dashboard
and
the
conclusion
is
just
thank
you
thumbs
up.
Clapping
emoji,
because
I've
had
a
really
great
time
and
and
I
hope
that
the
onboarding
issue
information
that
we
can
take
that
and
have
it
be
useful
in
the
future,
forget
lab
and
now
I
kind
of
want.
Does
anyone
have
any
more
questions?
I,
don't
I
know
everyone
is
super
busy,
and
this
this
is
a
really
short
presentation.
A
B
Eugenia
I
was
gonna.
Ask
you
like
I'm,
really
curious
about
your
experience
as
an
intern.
So
what
would
you
say
you
know
coming
into
the
internship
and
going
out
what
would
you
say:
you're
like
some
of
the
big,
maybe
aha
or
lightbulbs,
just
in
your
growth
as
an
analyst
and
kind
of
your
your
growth
and
your
skill
set,
you
know
just
kind
of
what
what
what
are
the
big
takeaways
for
for
you.
That's.
A
Just
like
general
cumbersome,
like
I,
wasn't
working
with
you
know,
state-of-the-art
systems
and
so
I
think
one
of
the
moments
I
had
was
that
we,
you
know
our
biggest
challenge,
isn't
that
we,
you
know,
get
the
data,
do
the
analysis
like
put
it
away?
It's
like
this
data,
always
changing,
and
you
know
sometimes
it's
it's
not
even
you
know
the
data
changing
in
terms
of
like
constantly
being
updated,
but
sometimes
you
know
the
structure
the
way
the
data
is
stored,
changes
and
then
you
have
to
go
back.
A
You,
as
an
analyst
need
to
be
aware
of
all
of
kind
of
the
underlying
factors
of
like
what
is
informing.
You
know
whatever
analysis
it
is
that
you're
trying
to
perform
and
being
able.
You
know
to
speak
to
you
know.
Why
is
this
number
wrong
because
of
some
kind
of
error?
That's
more
insider,
being
able
to
understand
that
and
identify
that.
A
A
A
B
A
A
A
Public
mistake
is
like
a
learning
opportunity,
not
only
for
yourself
but
for
everyone
else,
and
so
I
was
getting
used
to
the
idea
that
instead
of
slacking,
you
specifically
Emily
asking
you
like
is
this.
What
I
should
put
in
my
issue?
It's
like?
No,
you
should
just.
It
was
like
understanding
that
I
just
make
the
issue
and
then,
if
there's
something,
that's
missing,
tell
me
on
the
issue
and
it
kind
of
this
being
public
about
the
learning
process.
A
A
A
Useful
or
just
productive,
I
guess
as
soon
as
possible
and
not
to
kind
of
get
bogged
down
with
you
know
the
number
of
tasks
I
do
think
that,
like
a
lot
of
what
the
onboarding
issue
covers
completely
necessary,
and
you
know
it's
something
that
you
would,
if
you
were
in
a
actual
workspace,
you
would
kind
of
go
through
and
have
a
meeting
with
HR.
And
then
you
would
sign
documents
and
it
would
be.
You
know
that
would
just
one
day
of
your
life
and
you
forward
so
I
think
really
like.
A
Ideally
I
would
I
would
love
for
this
to
to
kind
of
inform
the
way
that,
like
just
remote
companies
on
board
people
in
general,
I
mean
I,
know
that
we're
at
like
a
very
smallest
point
of
that
analysis,
but
I
think
like
moving
forward.
We
could
see
like
how
to
best
do
it
and
then
kind
of
be
a
you
know,
a
role
model
in
that
way.
So.