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From YouTube: Humans of DataHub: Patrick Franco Braz
Description
Elizabeth Cohen sat down with Patrick Franco Braz, Data Engineer at Hurb. Patrick shares how DataHub is driving best practices and cross-functional collaboration across Hurb, his love for the DataHub Community, and MORE!
Learn more about DataHub: https://datahubproject.io
Join us on Slack: http://slack.datahubproject.io
Follow us on Twitter: https://twitter.com/datahubproject
A
Hello,
everyone
and
welcome
to
our
next
installment
of
humans
of
data
hub.
You
may
have
noticed:
we've
been
on
a
bit
of
a
summer
hiatus,
we
can
call
it
and
we
are
so
excited
to
be
back
speaking
with
community
members
about
their
data
hub
journey,
and
today
we
are
joined
by
patrick
patrick,
thank
you
for
being
here
and
I
will
pass
it
to
you
to
introduce
yourself
where
you
work,
your
role
and
all
that
good
stuff,
hello.
B
Everyone
I'm
25
years
old.
I
live
in
here
january,
brazil,
so
I've
been
part
of
the
leaderhub
community
for
a
few
months
here
in
brazil.
I
assume
a
position
of
data
engineer
at
herb.
It's
more
specific.
I
I'm
now
assuming
a
position
like
a
data
platform
position,
so
I
have
to
take
care
about
our
dating
infrastructure
and
take
care
of
our
data.
Stack
is
olan.
B
A
B
Data
hub
and
we
started
to
study
the
tool
and
what
what
we,
what
kept
our
attention
was
that
we
can
control
the
access
to
the
on
the
platform
at
all,
and
the
data
hub
has
a
very
friendly
ui.
So
for
us
this
is
very
important.
Why,
internally,
we
have
a
self-service,
analytic
tutor
that
we
are
trying
to
express.
So
any
collaborator
can
access
the
two
to
find
the
assets
they
want.
So
data
hub.
It's
a
good
tool
to
bring
bring
this
future
inside
our
company.
B
How
can
I
say
bring
a
kind
of
a
central
repository
to
our
collaborators
can
find
the
data
they
want,
but
also
we
we
can
build
a
kind
of
source
of
truth
for
everything.
So
we
have
many
tools
on
our
deep
stack
and
we
are
creating
a
kind
of
metadata
synchronization
product
process.
So
with
the
data
team,
each
team,
like
ml
team,
use
some
tools,
data
engineers
and
tools
and
the
vi.
Analysis
and
other
teams
use
another
tools.
B
B
B
A
B
B
So
one
thing
that
is
important
for
us-
and
I
I
think
for
me,
in
my
opinion,
the
best
use
case
for
this
is
that
we
have.
We
use
a
data
quality
platform
called
anomalous
and
we
sync
every
metadata
from
their
own
data
hub.
So
our
collaborators
can
see
data
validation,
rules
on
the
data
sets
and
entirely
on
the
data
team.
We
can
see
with
lineage
and
impact
analysis
when
a
data
issue
occurs,
who
is
being
impacted
with
because
of
these
data
issues.
B
B
B
Everyone
is,
is
kind
of
trying
to
help
asking
a
lot
of
things,
and
this
is
very
important
because
I
can
learn
with
questions,
so
I
I
I
constantly
see
what
people
are
searching
for
infor
and
I
can
learn
with
that
when
the
data
hub
team
respond
for
some
trouble,
and
I
I
cannot,
I
appreciate
a
lot
this
kind
of
help,
and
now
I
think
that
I
help
I
have
the
power
to
help
too.
So
I,
like
this
kind
of
relation
like
a
helpful
creature.
So
for
me
this
is.
This
is
very
incredible.
A
Yeah,
absolutely
we
do
have
a
very
special
community
and
yeah
like
how
folks,
I
think,
initially
start
out
like
asking
a
lot
of
questions
and
then,
a
few
months
later,
like
we'll
see
them
in
slack
channels,
answering
other
people's
questions.
So
it
is
really
cool.
How
it
kind
of
yeah
just
creates
this.
A
B
So
I
talked
about
impact
analysis,
so
maybe
column
level
lineage
will
be
incredible
to
have
because,
as
I
said,
sometimes
we
have
to
change
some
some
transformation
tasks
and
we
do
not
change
all.
Sometimes
this
kind
of
a
small
change
in
some
columns
and
see
these
relation
in
this
granular
way
like
a
what
column
is
used
by
what
table
or
what
view
is
important,
and
it
will
be
incredible.
A
B
A
B
A
You
know
like
we
talked
about
a
few
minutes
ago,
but
there's
such
a
level
of
camaraderie
within
the
community
of
just
like
I
I
was
struggling
with
this
a
few
months
ago
and
now
let
me
like
help
you
through
and
then
the
last
question
is
one
of
my
favorite
questions
to
ask
our
community
members.
So
what
advice
would
you
give
to
someone
who
is
just
learning
about
data
hub
or
has
like
just
joined
the
data
hub
community?
A
B
That
has
a
lot
of
people
to
help
you,
but
the
documentation
has
a
lot
of
things
that
people
are
always
asking
on
slack
channel
and
you
can
only
read
for
like
a
trusted
source
and
you
can
do
everything
from
the
documentation.
So
my
my
first
advice
is
that
I
think
a
second
advice
is
try
to
try
harder
on
the
quick
start,
because
I
did
that
you
have
to
start
a
kind
of
a
local
environment.
B
B
A
B
A
B
Much
I
am
very
grateful
for
this
opportunity
and
I'm
grateful
to
because
my
company
helps
me
a
lot
giving
this
opportunity
to
be
part
of
the
leaderhub
community
and
my
team
to
I've
always
on
my
side.
Give
me
some
advice,
so
so
thanks
a
lot
for
the
community
to
help
me
and
thanks
for
everyone,
that's
behind
me
inside
my
company,
like
helping
me
to
be
possible.