►
From YouTube: DataHub 201: Impact Analysis
Description
Maggie Hays (Acryl Data) provides an overview of how you can leverage DataHub's Impact Analysis feature when trying to determine what my happen when you push a breaking change to your datasets during the May 2022 Town Hall.
Learn more about DataHub: https://datahubproject.io
Join us on Slack: http://slack.datahubproject.io
Follow us on Twitter: https://twitter.com/datahubproject
A
So
if
y'all
have
been
joining
town
halls
for
a
while
every
once
in
a
while,
we'll
have
data
hub
101,
where
we
kind
of
do
a
deep
dive
into
a
specific
feature.
This
time
around
we're
going
to
do
some
advanced
functionality
and
advanced
use
cases
within
data
hub
and
today
we're
going
to
talk
about
impact
analysis.
A
So,
for
the
sake
of
this,
we
are
going
to
talk
about
briefly
talk
about
a
fictional
company
called
long
tail
companions
where
every
pet
is
exceptional
and
in
long
tail
they
have
a
highly
fragmented
data
stack
so
within
their
adoptions
team.
Oh,
I
should
say
that
long
tail
companions
is
an
adoptions
agency
and
pets,
pet
supply
store,
and
so
within
their
organization
they
have
an
adoptions
team.
That
team
is
using
postgres
and
mongodb
for
their.
A
So
hopefully
this
is
a
you
know,
kind
of
a
familiar
landscape
for
you
all,
and
really
it's
just
it's
just
to
demonstrate
that
within
a
modern
data
stack,
there
are
a
lot
of
touch
points
across
a
lot
of
areas,
and
one
thing
that
is
that
could
be
really
difficult
to
answer
is:
if
I'm
going
to
make
a
change
in
a
production
application
schema.
What
does
that
impact
downstream?
So
maybe
someone
on
the
adoptions
team
is
saying
what
like
they
want
to
make
a
change
to
the
pet
profile
data
set.
A
But
what's
gonna
change
like
what's
gonna?
Be
impacted
by
that
so
with
data
hub.
We
have
this
idea
of
impact
analysis,
so
this
is
just
a
quick
screenshot
of
it
we'll
go
into
a
demo
in
a
second
but
ultimately
choose
your
choose.
Your
data
set
or
your
your
entity
that
you
want
to
augment
or
kind
of
proactively
understand
what
will
happen.
If
you
make
changes
to
it
and
then
we
can
go
into
the
impact
analysis
workflow.
A
Oh
that's
not
a
big
deal
at
all,
but
if
we
go
into
impact
analysis,
we
can
actually
start
to
see
that
downstream
of
all
of
that
are
65
charts,
17
dashboards,
10
data
sets
two
tasks
across
all
of
these
different
platforms,
so
we're
specifically
interested
in
looking
at
dashboards
that
are
going
to
be
impacted.
So
if
I
click,
if
I
filter
down
to
dashboards,
I
can
now
see
that
there
are
these
17
looker
dashboards
all
within
this
10th
degree
connection.
A
So
it's
10
steps
down
that
change
of
transformations,
and
I
now
have
a
cohesive
set
of
entities
that
I
know
might
be
impacted.
So
if
I
want
to
get
in
touch
with
the
owners
of
this,
I
can
quickly
download
a
summary
of
these
open
this
up
in
good
old
excel,
which
is
on
my
other
screen.
Here
we
go
and
what
you'll
see
is
both
the
the
urn
for
the
entity.
A
I
realize
this
is
a
little
bit
small.
Let
me
blow
this
up
for
you.
You
can
see
the
name
of
it,
it's
a
dashboard,
but
then
I
also
have
information
about
the
owners
that
that
the
owners
of
those
resources,
so
I
now
have
a
concrete
list
of
people
to
contact
and
I
can
be
proactive
in
my
communication
and
ask
them
or
start
to
collaborate
with
them
to
make
sure
that
any
of
the
changes
that
I
push
aren't
going
to
have
an
adverse
reaction
there.
A
Along
with
this,
we
also
have
information
around.
You
know
the
tags,
the
terms
and
then
also
explicit
links
out
to
those
entities,
so
you
can
literally
just
hand
this
off
to
someone
and
then
they
can
go.
Do
the
research
on
their
side
or
it
just
it
just
makes
it
so
much
easier
to
collaborate
so
yeah,
so
that's
it
for
for
impact
analysis.
This
is
one
that
I
know
personally.