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Description
Taufiq Ibrahim (Bizzy - Warung Pintar Group) shares Bizzy's experience choosing a data catalog and working closely with the DataHub open-source community
A
A
Now
we
are
serving
around
600
brands,
fmcg
brands
and
serving
around
230k
of
retailers,
fresh
indonesia.
So
actually
we
have
two
kind
of
business
here.
One
is
the
supply
side,
which
is
which
is
working
with
the
distributor
and
fmcg
brand,
and
the
other
thing
is
we
work
with
the
retail
part
with
the
we
call.
It
is
actually
in
in
initial
work
for
grocery
retailers,
yeah
thanks
yeah.
This
is
a
data
ecosystem
at
one
printer
group
and
busy.
A
So
we
have
several
legacy.
Let's
say
a
legacy
stack
coming
from
existing
platform
from
corporate
enterprises
like
sap,
but
we
also
have
more
modern
architecture
like
a
cloud-based
application.
So
we
have
like
a
mix
of
technology
stacks
like
you
can
see
that
we
have
airflow.
We
have,
as
it
still
have
ssis
here
and
then
we
broke
some
of
this
stack
into
operational
part
and
the
analytical
part,
and
also
we
have
operational
domain,
which
is
actually
the
erp
and
the
application
databases
we.
A
You
can
see
that
we
have
multiple
reporting
services
like
we
have
the
the
old
stack
like
legacy,
sql
server,
reporting
services,
we
have
metabase,
we
have
redash
and
also
we
have
jupiter
why
we
have
so
much
stack
here,
because
we
we've
been
through
multiple
merged
and
sales
and
we
need
to
maintain
most
of
it,
because
the
users
still
need
to
use
it.
That's
why
metadata
and
then
the
lineage
things
is
really
important
here.
A
So
we
can
understand
easier
for
all
the
data
yeah
next,
so
why
we
need
the
data
catalog
in
busy,
because
one
the
first
one
is.
We
have
like
endless
repeated
question
from
from
anyone
like
where
the
data
is
how
it
is
produced
who
owns
it,
and
the
question
is
like
repeated
every
day
from
different
person
and
we
we
we
keep
answering
it
and
then
it's
also
difficult
to
look
for
lineage
and
impact
analysis
like
because
we
have
lots
of
data
source
and
a
lot
of
reporting
that
use
the
the
data.
A
A
We
just
create
a
like
a
simple
manual
dead
lineage
on
cuba,
siege
and
then
we
move
to
to
do
some
poc
with
mhg
atlas,
but
we
found
that
it
was
too
complex
and
too
hadoop
at
the
time.
So
we
we
stopped
the
the
poc
and
then
we
also
doing
some
plc
with
amundsen,
but
at
the
time
it
wasn't
really
answering
what
we
need
and
then
actually
at
the
end
of
2020,
we
found
data
hub
and
then
we
start
doing
poc
and
then
development
with
data
hub
next.
A
It's
really
really
helpful.
The
the
documentation
was
really
helpful
and
then
the
other
features
that
we
are
really
love
is.
We
can
show
the
dashboard
link
from
the
app
and
then
right
click
to
it
and
click
to
it,
and
then
we
we
will
brought
right
into
the
the
the
dashboard
itself
and
then
now
we
have
the
the
role
based
access
and
we
can
limit
what
users
can
do.
That's
just
really
really
awesome
right.
Now
yeah
next.
A
A
We
just
push
it
directly
to
data
hub
mcs,
yeah
thanks,
so
why
we
develop
read
this
integration
because,
after
the
merge,
we
found
that
one
quinta
group
use
readers
a
lot
from
data
analysts
to
product
teams
to
hr
teams.
They
use
redash
a
lot,
they
practically
love
to
learn
sql
and
they
can
use
redash
quite
good
and
it's
actually
a
develop
based
on
the
superset
source
and
then
the
other
reason
is
actually
it
helped
the
plc
to
be
approved
internally
and
right
now.
A
B
A
Yeah
this
is
the
the
the
example
of
the
recipes
of
our
re
dash.
Is
you
can
find
it
in
the
documentation,
the
github?
Basically,
what
you
need
is
the
the
url
connection
of
the
radar
server
itself.
This
is
a
hosted,
I
know
not
the
hosted
three
dash,
but
this
is
the
open
source
one
and
we
need
the
api
key
and
then
we
can
limit
the
page
for
like
for
testing
purpose
by
default.
A
A
A
A
B
A
A
B
A
Data
hub
development
experience
coming
from
me
and
our
team:
actually,
the
contribution
for
connect
source
was
my
first
open
source
contribution
ever
actually
for
github
tastes,
yeah,
and
I
thought
that
the
community
is
very
welcoming
it's.
They
are
very
supportive.
I
even
got
some
private
message
and,
like
sushanka
asked
me
do
do
I
still
want
to
to
contribute
something
like
that.
It's
very
it's
very
supportive
yeah
and
the
documentation
is
very
helpful
like
how
to
add
new
ingestion
source.
A
We
are
still
in
p
assisted,
but
we
will
socialize
and
get
users
feedback
starting
from
next
week,
and
I
hope
that
this
will
give
impact
for
for
our
organization
and
expected
for
data
hub
yeah.
We
already
talked
about
the
lineage
for
the
large
graphs
and
then
we
also
interested
in
operational
data
quality
metrics,
something
like
lagging
metrics
and
then
row
count
something
like
that:
yeah
just
to
check
for
the
anomaly
on
daily
basis,
something
like
that
yeah.
That's
all
for
me.
Thank
you.
So
much.