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From YouTube: DataHub 201: Rolling out DataHub to Your Stakeholders
Description
Paul Logan shares tips and tricks to consider when rolling out DataHub to your stakeholders during the February'23 Town Hall.
Presentation Deck:
https://docs.google.com/presentation/d/1cFZ1hhMtuXM1yU5ZHvT2aTGT89pUg33dR5ckWEzskQY/edit?usp=sharing
Learn more about DataHub: https://datahubproject.io
Join us on Slack: http://slack.datahubproject.io
Follow us on Twitter: https://twitter.com/datahubproject
A
We
have
one
more
round
to
go
so
for
those
of
you
who
have
not
seen
a
data
Hub,
101
or
2-1
before
every
once
in
a
while.
We
like
to
make
sure
that
folks
kind
of
have
understand
the
basics
of
data
Hub
understand
some
of
the
more
advanced
features
of
data
Hub,
so
Paul's
going
to
walk
us
through
some
tips
for
how
to
roll
out
data
Hub
within
your
organization.
B
Yeah,
thank
you
magni.
All
these
are.
These
are
inspired
from
conversations
we
have
with
the
community
and
customers
trackable
data,
so
yeah,
let's
just
get
going,
so
this
is
just
five
tips
to
roll
out
data
Hub
to
your
organization
after
you've
deployed.
So
the
first
one
is
educate
and
deprecate
around
data
catalogs.
So
this
is
kind
of
a
decision
tree.
B
B
The
other
thing
is:
if
you
previously
have
a
data
Hub,
a
data
catalog
create
a
deprecation
plan
forward,
communicate
hard
deadlines
stages
where
you'll
a
stop
having
an
API
disable
the
UI
or
fully
deprecate,
make
use
of
banners
in
that
tool
and
slack
announcements
to
increase
awareness
and
use
soft
and
hard
deadlines.
Soft
deadlines,
like
redirecting
to
data
hub
from
your
old
tool
and
hard
deadlines
like
actually
tearing
down
infrastructure
when
the
functionality
has
been
replaced
by
data
hub
also,
you
know
pair
it
with
other
onboarding
techniques.
B
Aha
moments,
key
learnings
from
them
and
use
those
in
quotes
to
broadcast
to
your
larger
audience,
help
them
teach
their
teams
and
onboard
them
individually.
This
is
sort
of
the
flywheel
of
of
creating
more
and
more
people
who
are
using
data
Hub
correctly
in
your
organization
and
not
everyone
has
this
option
but
Etsy,
for
example,
had
a
data
Discovery
team
that
handled
all
of
the
adjustions
and
custom
scripting,
which
makes
it
really
easy
to
create
critical
massive
data
within
your
data
Hub
and
make
it
more
useful.
B
Fourth,
create
regular
onboarding
workshops
and
office
hours,
make
people's
lives
easier,
help
them
walk
away
with
that
new
knowledge,
schedule,
presentations
and
demos
during
learning
weeks
or
and
create
make
sure
you
get
on
the
docket
for
internal
meetups
and
lean
on
your
Champions
to
find
that
story
that
sticks
with
users,
for
example,
Etsy
found
that
that
data
governance
conversation
was
really
compelling,
and
it
was
the
data.
Hub
was
the
perfect
solution
for
this
problem.
B
Finally,
establishing
goal
posts,
timelines
for
daily
active
users
and
and
how
many
users
you've
onboarded
documents,
like
the
state
of
your
instance
at
regular
intervals,
take
shop
snapshots.
So
you
can
see
how
far
you've
come,
encourage
governance
expectations
like
adding
ownership
to
assets,
creating
glossary
terms
within
domains
or
making
all
of
the
lineage
populated
for
certain
tools
and
work
with
your
stakeholders
to
identify
those
new
use
cases.
B
That
adds
value,
but
don't
describe
anything,
review
those
sources
and
make
sure
that
you're
not
interested
in
really
poorly
managed
things
or
blank
data
sets,
so
that
you're
not
causing
friction
when
people
go
in
looking
for
the
thing
and
can't
find
it
or
find
that
it's
not
right
and
don't
wait
until
the
metadata
is
perfect.
Really
data
Hub
thrives
when
you
encourage
your
users
to
take
ownership
and
start
filling
in
those
gaps
with
glossary
terms
and
in
other
populated
metadata.