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From YouTube: Humans of DataHub - Kartik Darapuneni
Description
Elizabeth Cohen and Maggie Hays sat down with Kartik Darapuneni, Tech Lead of the Data Applications team at Included Health. Listen in to hear Kartik's experience implementing DataHub in his organization while collaborating with the vibrant DataHub Community!
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B
B
And
so
when
we
first
started
down
the
data
data
platform
creation
journey,
I'd
say
this
is
about
two
years
ago.
We
really
built
the
experience
for
you
know.
How
do
you,
author
new
data,
sets?
How
do
you
get
new
data
into
the
platform
and
so
forth,
and
so
naturally,
that
kind
of
evolved
into
well?
We
now
have
thousands
of
data
sets
that
people
are
creating
and
leveraging,
and
so
we
want
to
continue
the
reuse
of
great
data,
and
so
how
do
we
kind
of
surface
that
information?
How
do
we
make
data
discoverable
and
searchable?
A
A
B
Maybe,
to
step,
take
a
step
back
and
answer
a
different
question
which
is
like:
how
do
I
think
about
open
source
tools
which
might
be
this
question
when
I
look
at
like
all
the
tools
that
are
in
the
open
source
community,
I
kind
of
think
about
it
in
the
sense
of
oh
here's
like
the
building
blocks
that
we
have
to.
You
know
further
our
own,
like
mission,
and
so
when
I
think
about
data
hub,
I
think
about
it
from
like
the
pieces
that
are
available
right.
So
it's
like
a
search
platform.
B
The
ability
to
like
add
custom
like
facets,
really
easily
and
add
new
entities
in
a
scalable
way,
and
so
once
we're
kind
of
at
that
phase
where
it's
like.
Well,
okay,
what
are
all
the
core
components
we
need
to
bring
in
to
make
all
of
the
data
discoverable,
and
so
we're
kind
of
like
most
of
the
way
through
that
particular
phase.
And
now
what
we're
thinking
about
is
what
is
the
user
experience
for
when
they
land
in
data
hub
right
so
sure
the
search
bar
is,
is
not
the
best
experience
for
everyone?
B
It's
probably
you
know
enough
for
most
companies,
but
you
know
I,
the
company
I
work
at
is
in
healthcare,
and
the
data
is,
I
would
say,
very,
like
nested
very,
like
difficult
to
understand
in
the
breadth
of
the
data
that
we
have,
and
so
we
don't
want
people
just
searching
for
random
terms
because,
like
how
do
you
even
find
the
right
term?
That's
often
difficult
right.
A
B
A
No,
that's
awesome
and
I
love
I
love
this
idea
of
you
know
we
talk
about
this
a
lot
kind
of
internally
and
I
talked
to
a
lot
of
folks
in
the
community
about
how
you
know
a
tool
or
a
platform
can
only
take
you
so
far
like
you
really
need
to
tailor
it
for
your
use
cases
or
tailor
it
for
your
stack
or
your
like,
really
like
the
actions
that
you
want
people
to
drive.
So
I
love.
A
B
B
There's
there's
lots
of
like
individual
workflows
that
it
has
really
enabled
for
us.
You
know
one
of
the
big
like
challenges
with
data,
as
it
starts
to
sprawl
out
into
different
systems
that
you
have
right.
So
you
know,
most
companies
have
like
a
bi
tool
of
choice.
They've
got
like
some
way
of
authoring
data
and
then
you've
got
the
raw
data
and
then
some
sort
of
execution
engine
very
generically
speaking
and
so
what
starts
to
happen
is
there?
Is
this
like
cognitive
overload?
B
B
Oh,
you
know
I
want
to
add
a
new
field
here,
but
how
will
it
impact
the
downstream
data
sets
or
like
downstream
reporting,
that's
kind
of
like
what
we've
enabled
today,
but
and
so
when,
when
I
think
about
the
the
impact
analysis
is
like
a
great
example
where
you
know
you're
like
oh,
I
want
to
make
this
change.
I
want
to
quickly
see
all
dashboards,
but.
B
Know
sit
through
and,
like
click,
each
of
the
lineage
extensions
to
find
like
final
places
used.
So
that's
one
place.
It's
really
helped
us
out,
obviously
like
surfacing
all
of
the
metadata
of
like
who
the
owner
is
the
descriptions
and
things
like
that
has
really
been
useful,
and
so
we
want
to
take
that
like
one
step
further
and
say
like
well,
what
is
like
good
descriptions,
look
like
right
and
so
like
we're
still
in
the
process
of
figuring
out
a
lot
of
things,
but
we
have
the
building
blocks.
B
A
B
B
A
B
So
this
isn't
as
useful,
but
we
know
we'll
eventually
get
there
sure
to
say
like
I
can
see
where
you're
going
and
I
can
see
how
we
get
there.
So
it's
this
interesting
dynamic
that
we're
you're,
like
oh,
like
yeah,
like
we
can
grow
in
in
this
way,
and
that's
how
the
best
of
the
teams
who
use
data
are
thinking
about
it
right.
So
it
helps
us
give
perspective
the
other,
like
part,
that
I
love
is.
B
B
B
I
think
us
trust
that,
like
you
know
when
we
do
deploy
and
we
run
into
problems,
sure
there's
like
a
path
forward
where
we're
not
just
going
to
be
stuck,
there's
like
other
people
who
have
kind
of
like
probably
stumbled
into
it
or
are
looking
at
the
problem,
sure
so
yeah.
I
think
those
are
the
two
things
that
I
really
like
about
the
community.
B
B
So
it's
the
it's
the
work
that
the
team
did
around
surfacing
the
great
expectations,
validations
and
status
of
tables.
Right,
yes,
and
so
this
is
I'll,
go
back
to
the
building
block,
like
analogy
where
we
see
this
as
a
building
block
where
we're
like
well
yeah,
there's
some
like
expectations
that
are
set
in
the
table.
But
like
could
you
do
like
a
little
bit
more
with
that?
B
B
B
B
We
can't
have
people
like
sitting
and
looking
at
dashboards
for
like
hours,
trying
to
figure
out.
Is
this
like
up
to
date?
So
that's
one
of
the
features
that
I'm
kind
of
most
excited
about
leveraging
and
then
the
the
second
one
is
like
actions.
I
know
it
just
came
out.
Yes,
but
I
see
a
lot
of
potential.
A
Yeah
we're
I'm,
I'm
really
excited,
I
think,
on
the
the
kind
of
like
quality
like
data
quality
score.
This
comes
up
a
lot
and
I
think
it's
something
that
I'm
personally
excited
for
us
to
figure
out
how
to
tackle
it
in
a
building
blocks.
Kind
of
way
right
where
it's
like
data
hub,
the
open
source
platform
doesn't
have
a
strong
opinion
about
what
what
makes
for
good
data.
B
A
B
A
B
B
A
B
What
I
see
is
like
this
plug-in
based
system
that
someone's
going
to
build
for
each
of
these
different
tools
and
now
you've
like
enabled
scalability
of
data
hub,
and
it's
not
just
like
well.
If
the
data
hub
team
rolls
out
it's
like.
Oh
it's
with
the
you
know,
50
or
I
think
it's
like
a
thousand
plus
members
and
data
hub
slack
now.
But
you
know
three.
B
B
A
Yeah,
so
I
know
there's
a
lot
that
that
you
all
are
actively
doing
with
data
hub.
I
know
that
you
know
we
talked
about
like
validations
action
frameworks
as
some
exciting
things,
but
I'm
curious
kind
of
like
for
the
remainder
of
2022,
maybe
even
going
into
2023
like
what.
What
are
you
excited
about
seeing
within
the
data
hub
community
like
what
would
what
is
success
or
you
know,
kind
of
like
meaningful
growth.
Look
like
from
your
perspective.