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How to Build Data Strategies That Actually Work · Private Equity Data Guy

0:00
Claude
0:00
or
0:00
GPT,
0:01
and
0:01
it
0:01
becomes
0:01
part
0:02
of
0:02
this
0:02
big
0:02
AI
0:03
brain
0:03
and
0:03
part
0:03
of
0:03
its
0:04
knowledge.
0:04
Now,
0:05
if
0:05
I'm
0:05
in
0:05
marketing,
0:05
all
0:06
I'm
0:06
doing
0:06
all
0:06
day
0:06
is
0:06
talking
0:07
about
0:07
how
0:07
great
0:07
my
0:08
products
0:08
are,
0:08
how
0:08
great
0:08
my
0:09
company
0:09
is,
0:09
what
0:09
a
0:09
good
0:10
place
0:10
this
0:10
is
0:10
to
0:10
work,
0:11
how
0:12
the
0:12
things
0:12
we
0:12
do
0:12
can
0:13
change
0:13
your
0:13
lives.
0:13
Like,
0:14
don't
0:14
you
0:14
want
0:14
that
0:14
in
0:15
there?
0:15
GPT
0:15
or
0:15
cloud
0:16
or
0:16
whatever,
0:17
it
0:17
just
0:17
gets
0:18
the
0:18
first
0:18
things
0:18
that
0:18
come
0:19
up
0:19
on
0:19
the
0:19
Internet
0:19
and
0:20
super
0:20
generic
0:21
crap.
0:22
Companies
0:23
are
0:23
buying
0:23
these
0:24
things
0:24
and
0:24
think
0:25
it
0:25
does,
0:25
all
0:26
without
0:26
thinking,
0:26
oh,
0:26
you
0:27
actually
0:27
have
0:27
to
0:27
think
0:27
about
0:27
this
0:28
strategically,
0:28
about
0:28
why
0:29
I'm
0:29
using
0:29
this
0:29
and
0:29
how
0:30
to
0:30
use
0:30
it
0:30
better.
0:30
You're
0:31
listening
0:31
to
0:31
the
0:31
Transformed
0:32
with
0:32
Data
0:32
podcast
0:33
with
0:33
Graham
0:33
Crawford,
0:34
CEO
0:35
of
0:35
Crawford
0:35
McMillan.
0:36
Graham
0:36
is
0:37
here
0:37
to
0:37
share
0:37
something
0:37
he's
0:37
genuinely
0:38
passionate
0:38
about.
0:39
He's
0:39
going
0:39
to
0:39
show
0:39
you
0:40
how
0:40
data
0:40
can
0:40
completely
0:41
change
0:41
the
0:42
outcome
0:42
for
0:42
both
0:42
people
0:42
and
0:43
businesses.
0:44
In
0:44
each
0:44
episode,
0:44
he
0:45
sits
0:45
down
0:45
with
0:45
real
0:45
people
0:46
who've
0:46
done
0:46
incredible
0:47
things
0:47
with
0:47
data.
0:48
But
0:48
don't
0:48
worry,
0:49
these
0:49
aren't
0:49
your
0:49
typical
0:50
dry
0:50
case
0:50
studies.
0:51
Graham
0:52
and
0:52
his
0:52
guests
0:52
bring
0:52
you
0:53
stories
0:53
about
0:53
leaders
0:53
and
0:54
innovators
0:54
who
0:54
saw
0:55
something
0:55
in
0:55
their
0:55
data
0:56
that
0:56
sparked
0:56
a
0:56
brand
0:57
new
0:57
reality.
0:58
These
0:58
are
0:58
changes
0:59
that
0:59
tore
0:59
through
0:59
entire
1:00
industries,
1:00
upended
1:01
company
1:01
cultures,
1:02
and
1:02
sometimes
1:03
even
1:03
changed
1:04
lives.
1:05
So
1:05
whether
1:05
you're
1:05
a
1:05
data
1:06
enthusiast
1:06
or
1:07
just
1:07
curious
1:07
about
1:08
how
1:08
to
1:08
find
1:08
the
1:08
truth
1:09
in
1:09
your
1:09
data,
1:10
join
1:10
Graham
1:10
as
1:11
he
1:11
discovers
1:11
how
1:12
data
1:12
becomes
1:12
more
1:13
than
1:13
just
1:13
numbers.
1:14
It
1:14
becomes
1:15
the
1:15
spark
1:15
that
1:16
ignites
1:16
real,
1:17
meaningful
1:17
change.
1:18
Let's
1:19
get
1:19
started.
1:19
Thanks
1:20
for
1:20
listening.
1:20
Most
1:21
data
1:21
strategies
1:21
die
1:22
in
1:22
Google
1:22
Docs
1:23
Buried
1:23
by
1:23
misalignment,
1:24
jargon
1:25
and
1:25
the
1:25
chaos
1:25
of
1:25
business
1:26
reality,
1:27
Dylan
1:27
Anderson
1:27
is
1:28
on
1:28
a
1:28
mission
1:28
to
1:28
change
1:28
that.
1:29
As
1:30
head
1:30
of
1:30
Data
1:30
Strategy
1:31
at
1:31
Profusion
1:31
and
1:32
creator
1:32
of
1:32
the
1:32
Data
1:33
Ecosystem
1:33
newsletter,
1:34
Dylan
1:35
helps
1:35
organizations
1:36
stop
1:36
talking
1:36
about
1:36
data
1:37
and
1:37
start
1:37
building
1:38
systems
1:38
that
1:38
actually
1:39
deliver.
1:40
His
1:40
work
1:40
translating
1:41
complex
1:41
AI
1:41
and
1:42
analytics
1:42
into
1:42
business
1:42
outcomes
1:43
has
1:43
earned
1:44
him
1:44
a
1:44
nomination
1:44
for
1:44
AI
1:45
Strategist
1:45
of
1:46
the
1:46
Year
1:46
at
1:46
the
1:46
Agentiq
1:47
innovation
1:47
summit.
1:48
With
1:48
7,000
1:49
plus
1:49
subscribers
1:50
and
1:50
a
1:50
cult
1:51
following
1:51
amongst
1:51
data
1:52
leaders,
1:52
including
1:52
me,
1:53
Diller's
1:54
writing
1:54
cuts
1:54
through
1:54
the
1:55
noise,
1:55
showing
1:55
exactly
1:56
how
1:56
to
1:56
bridge
1:56
the
1:56
gap
1:56
between
1:57
architecture
1:57
and
1:57
action.
1:58
Today
1:58
we're
1:59
getting
1:59
into
1:59
why
2:00
most
2:00
data
2:00
strategies
2:01
fail
2:01
and
2:01
how
2:01
to
2:02
build
2:02
one
2:02
that
2:02
sticks,
2:03
the
2:03
emerging
2:03
role
2:03
of
2:04
AI
2:04
in
2:04
data
2:04
organizations
2:05
and
2:06
how
2:06
to
2:06
turn
2:06
technical
2:07
vision
2:07
into
2:07
commercial
2:08
reality.
2:08
Ever
2:09
struggled
2:09
with
2:09
one
2:10
of
2:10
those?
2:10
Or
2:10
to
2:11
get
2:11
buy
2:11
in?
2:11
Or
2:11
to
2:11
build
2:12
momentum
2:12
with
2:12
your
2:12
data?
2:13
This
2:13
one's
2:14
for
2:14
you.
2:14
Here's
2:15
Dylan
2:15
Anderson.
2:15
Hi
2:16
everybody.
2:16
Good
2:17
to
2:17
be
2:17
on
2:17
the
2:17
show.
2:18
Welcome,
2:18
welcome.
2:19
Good
2:19
to
2:19
have
2:19
you.
2:20
Good
2:20
to
2:20
have
2:20
you,
2:20
Dylan.
2:21
Good
2:21
to
2:22
chat
2:23
with
2:23
you
2:23
again.
2:23
From
2:24
kind
2:24
of
2:25
opposite
2:25
countries
2:25
or
2:26
opposite
2:26
continents
2:27
position.
2:28
So
2:29
you
2:29
were
2:29
just
2:29
telling
2:29
me
2:29
how
2:30
is
2:30
London
2:30
this
2:31
time
2:31
of
2:31
year?
2:31
It
2:32
is
2:32
very
2:32
hot
2:33
right
2:33
now,
2:34
but
2:34
it
2:34
is
2:35
beautiful
2:35
and
2:36
London
2:36
summers
2:37
are
2:37
awesome
2:38
because
2:38
there's
2:38
so
2:39
much
2:39
to
2:39
do
2:39
in
2:39
London.
2:40
There's
2:40
so
2:40
much
2:40
going
2:41
on.
2:41
I've
2:41
got
2:41
like
2:42
four
2:42
data
2:43
events
2:43
next
2:43
week
2:43
in
2:44
the
2:44
sign,
2:44
including
2:44
my
2:44
other
2:45
non
2:45
data
2:46
related
2:46
events.
2:46
So
2:47
it
2:47
keeps
2:48
you
2:48
busy
2:48
but
2:49
when
2:49
the
2:49
weather's
2:49
nice
2:50
and
2:50
it's
2:50
not
2:50
rainy,
2:51
it's
2:51
gorgeous.
2:52
Non
2:52
data
2:52
events.
2:53
How
2:53
dare
2:53
you.
2:53
How
2:54
dare
2:54
you.
2:56
Is
2:56
it
2:56
Celsius
2:57
hot
2:57
or
2:57
Fahrenheit
2:57
hot?
2:59
I
3:00
don't
3:00
do
3:00
Fahrenheit
3:00
so
3:01
I
3:01
only
3:01
know
3:01
Celsius.
3:02
I
3:02
haven't
3:02
done
3:02
that
3:03
data
3:03
conversion
3:04
in
3:04
my
3:04
head
3:04
yet.
3:05
There
3:05
you
3:05
go.
3:05
And
3:06
we'll
3:06
have
3:06
to
3:06
build
3:06
a
3:06
product
3:06
for
3:07
it.
3:08
I
3:08
love
3:09
it.
3:09
Yeah,
3:09
in
3:09
a
3:09
busy
3:09
time
3:09
of
3:10
year
3:11
with
3:11
the
3:11
data
3:12
events
3:12
and
3:12
I
3:13
can
3:13
understand
3:13
why
3:13
you're
3:13
in
3:14
or
3:14
why
3:15
you're
3:15
in
3:15
so
3:15
much
3:16
demand
3:16
for
3:16
those.
3:17
So
3:17
you
3:18
know,
3:18
last
3:18
time
3:18
we
3:18
talked
3:19
it
3:19
was
3:19
as
3:19
part
3:19
of
3:20
a
3:20
research
3:20
study
3:21
that
3:21
you're
3:21
doing
3:21
and
3:21
I
3:22
think
3:22
you
3:22
were
3:22
speaking
3:22
to
3:22
a
3:23
large
3:23
number
3:23
of
3:24
data
3:25
leaders.
3:25
How
3:26
many
3:26
was
3:26
it
3:26
you
3:26
spoke
3:26
to
3:27
again?
3:27
It
3:27
was
3:27
a
3:27
big
3:27
chunk,
3:28
right?
3:28
Yeah.
3:29
So
3:29
I
3:29
ended
3:29
up
3:29
speaking
3:30
to
3:30
about
3:30
25
3:30
to
3:31
30.
3:31
And
3:32
what
3:33
it
3:33
was,
3:33
just
3:33
give
3:34
it
3:34
a
3:34
bit
3:34
more
3:34
context
3:35
on
3:35
it
3:35
is
3:36
me
3:36
just
3:36
having
3:36
conversations
3:37
to
3:38
understand
3:39
what
3:39
data
3:40
leaders
3:40
are
3:40
facing,
3:40
what
3:41
challenges
3:41
that
3:42
they're,
3:43
that
3:43
they're
3:43
facing
3:44
in
3:44
their
3:44
organizations,
3:45
what
3:45
opportunities
3:46
they
3:46
see
3:46
in
3:47
the
3:47
data
3:47
and
3:48
AI
3:48
space
3:49
and
3:49
kind
3:49
of
3:50
also
3:50
some
3:50
career
3:51
learnings
3:51
that
3:51
they
3:51
share.
3:51
Like
3:52
what,
3:52
what
3:52
has
3:53
helped
3:54
you
3:54
get
3:54
to
3:54
where
3:55
you
3:55
are
3:55
and
3:55
what
3:55
success
3:56
has
3:56
really
3:57
can
3:58
you,
3:58
can
3:58
you
3:58
speak
3:58
to.
3:59
And
4:00
right
4:00
now
4:00
I'm
4:01
putting
4:01
together
4:01
the
4:02
report
4:02
on
4:02
it
4:02
and
4:03
hoping
4:03
to
4:03
send
4:03
back
4:03
to
4:04
all
4:04
those
4:04
leaders
4:04
and
4:04
then
4:04
I
4:05
will
4:05
be
4:05
sharing
4:06
elements
4:06
of
4:07
that
4:08
ongoing
4:09
as
4:10
the
4:10
future
4:10
goes
4:10
along.
4:11
And
4:11
you
4:12
know,
4:13
having
4:13
spoken
4:14
to
4:14
all
4:14
of
4:14
those
4:14
data
4:14
leaders,
4:15
you
4:15
know
4:16
it
4:16
would
4:16
be
4:17
rude
4:17
of
4:17
me
4:17
not
4:17
to
4:17
ask
4:17
for
4:17
a
4:18
little
4:18
bit
4:18
of
4:18
a
4:18
scoop.
4:19
So
4:19
like.
4:20
But
4:20
it's
4:21
there
4:21
something
4:22
or
4:22
a
4:22
theme
4:23
that
4:23
emerged
4:23
that
4:23
really
4:24
kind
4:24
of
4:24
surprised
4:25
you?
4:25
I
4:26
think
4:26
the
4:26
biggest
4:26
theme
4:27
that
4:27
surprised
4:27
me
4:28
a
4:28
lot
4:29
of
4:29
it
4:29
was,
4:30
is
4:30
pretty
4:30
standard.
4:31
So
4:31
the
4:31
standard
4:32
stuff
4:32
I'd
4:32
say
4:33
would
4:33
be
4:33
like
4:33
focus
4:34
on
4:34
the
4:34
business
4:34
value
4:34
and
4:35
the
4:35
business
4:35
outcomes,
4:36
otherwise
4:36
you're
4:36
not
4:36
going
4:36
to
4:37
succeed.
4:38
People
4:38
are
4:38
kind
4:39
of
4:39
kept
4:39
up
4:39
at
4:39
night
4:40
by
4:40
the
4:40
fact
4:40
that
4:40
like
4:41
they
4:41
have
4:42
so
4:42
much
4:43
work
4:43
doing
4:44
work
4:44
to
4:45
convince
4:46
business
4:46
stakeholders
4:47
and
4:47
the
4:47
executive
4:48
of
4:48
what
4:48
they're
4:48
doing.
4:49
So
4:49
those
4:49
kinds
4:49
of
4:50
things
4:50
I
4:50
expected.
4:51
The
4:52
one
4:52
surprise
4:52
actually
4:53
that
4:53
I
4:53
found
4:53
was
4:54
what
4:54
people
4:54
are
4:54
excited
4:54
about,
4:55
what
4:55
opportunities
4:55
people
4:56
see.
4:56
People
4:57
did
4:57
mention
4:57
AI,
4:57
but
4:58
they
4:58
didn't
4:58
mention
4:58
it
4:58
like
4:59
agentic
4:59
AI
5:00
or
5:00
mcp.
5:01
They
5:01
were
5:02
like,
5:02
I'm
5:02
really
5:03
excited
5:03
for
5:03
AI
5:03
to
5:04
help
5:04
clean
5:04
our
5:04
data
5:04
and
5:05
improve
5:05
our
5:05
data
5:05
quality.
5:06
Or
5:06
I'm
5:06
excited
5:07
for
5:07
AI
5:07
to
5:07
improve
5:08
our
5:08
BI
5:08
dashboards
5:09
and
5:09
make
5:10
them
5:10
a
5:10
bit
5:10
more
5:10
insightful
5:11
and
5:11
like
5:12
those
5:12
kinds
5:12
of
5:12
things.
5:14
You're
5:15
like,
5:15
yeah,
5:15
that
5:15
makes
5:16
sense.
5:16
Most
5:16
these
5:17
organizations
5:17
aren't
5:18
at
5:18
like
5:18
the
5:18
speed
5:20
of,
5:20
of
5:21
LinkedIn
5:21
for
5:21
example.
5:22
LinkedIn
5:22
like
5:23
to,
5:23
to
5:23
think
5:24
that
5:24
we're
5:25
way
5:25
down
5:25
the
5:25
line
5:26
when
5:26
we're
5:26
actually
5:26
like
5:27
most
5:27
organizations
5:28
are
5:28
way
5:28
behind
5:29
that.
5:29
And,
5:30
and
5:30
this
5:30
kind
5:31
of
5:31
helps
5:31
reassure
5:32
what
5:32
are
5:32
we
5:33
actually
5:33
looking
5:33
for
5:34
in
5:34
new
5:34
technology
5:35
and
5:35
what
5:36
benefit
5:36
is
5:37
that
5:37
actually
5:37
going
5:37
to
5:38
drive?
5:38
And
5:38
for
5:38
most
5:39
organizations
5:39
it
5:39
was
5:40
just
5:40
using
5:41
AI
5:41
to
5:41
improve
5:44
the
5:44
existing
5:44
stack
5:45
and
5:45
the
5:45
existing
5:46
infrastructure.
5:47
Yeah,
5:48
AI
5:49
is
5:50
I
5:50
think
5:51
a
5:51
RL
5:51
course
5:52
in
5:52
the
5:52
data
5:52
quality
5:53
realm
5:54
in
5:54
particular.
5:54
And
5:55
I
5:55
think
5:56
including
5:56
the
5:57
human
5:57
in
5:57
the
5:57
loop
5:57
and
5:57
using
5:58
it
5:58
to
5:58
make
5:58
sure
5:59
that
5:59
your
5:59
data's
5:59
present
6:00
and
6:00
high
6:01
quality
6:01
and
6:02
correct
6:02
and
6:03
presented
6:03
the
6:03
right
6:04
way,
6:04
I
6:04
think
6:05
is
6:05
going
6:05
to
6:05
be
6:06
a
6:06
real
6:06
cool
6:06
way
6:06
of
6:07
doing
6:07
it.
6:07
But
6:07
I'm
6:08
going
6:08
to
6:08
come
6:08
back
6:08
to
6:08
the
6:09
MCP
6:09
and
6:10
agentix
6:10
stuff
6:11
and
6:12
this
6:12
is
6:12
one
6:12
of
6:12
my
6:12
favorite
6:12
things
6:13
to
6:13
hop
6:13
on
6:13
about.
6:14
I
6:14
see
6:14
people
6:14
using
6:15
Zapier
6:16
Flows
6:16
and
6:16
NAN
6:17
and
6:17
whatever
6:17
else
6:18
and
6:18
don't
6:18
get
6:18
me
6:19
wrong,
6:19
it's
6:19
super
6:19
cool
6:19
and
6:19
I
6:20
play
6:20
with
6:20
these
6:20
things
6:20
myself,
6:21
but
6:22
I
6:22
couldn't
6:22
be
6:23
further
6:23
from
6:23
wanting
6:23
to
6:23
deploy
6:24
that
6:24
as
6:24
part
6:24
of
6:24
an
6:24
enterprise
6:25
data
6:25
flow
6:26
or
6:26
an
6:26
enterprise
6:26
data
6:27
architecture
6:28
string
6:28
seven
6:29
different
6:29
platforms
6:30
together
6:31
with
6:31
the
6:31
Zapier
6:32
string
6:32
and
6:32
then
6:33
hope
6:33
that
6:33
all
6:33
the
6:33
APIs
6:34
stay
6:34
the
6:34
same
6:34
and
6:34
hope
6:34
the
6:35
Zapier
6:35
doesn't
6:35
fall
6:35
down.
6:36
It's
6:36
so
6:36
wildly
6:37
off
6:37
piece
6:37
to
6:37
me
6:37
that
6:39
people
6:39
think
6:39
that
6:39
AI
6:40
might
6:40
be
6:40
applied
6:40
in
6:40
that
6:41
way.
6:41
What
6:41
are
6:41
your
6:41
thoughts
6:42
on
6:42
that?
6:42
Yeah,
6:42
it's
6:42
funny,
6:43
it
6:43
reminds
6:43
me
6:43
of
6:43
actually
6:44
something
6:44
I
6:44
saw
6:44
the
6:44
other
6:44
day
6:45
on
6:45
LinkedIn
6:46
and
6:46
about
6:46
how
6:47
I
6:47
think
6:47
someone
6:48
asked
6:48
all
6:48
these
6:49
corporate
6:49
leaders
6:49
of
6:50
how
6:50
many
6:50
have
6:50
actually
6:51
used
6:51
some
6:51
of
6:51
these
6:52
small
6:52
AI
6:52
startups
6:53
and
6:53
enacted
6:54
it
6:54
in
6:54
the
6:54
organizations
6:55
and
6:56
pretty
6:56
much
6:57
all
6:57
of
6:57
them
6:57
were
6:57
like,
6:58
no,
6:58
we
6:58
can't,
6:59
because
6:59
compliance
7:00
issues,
7:00
security,
7:01
privacy,
7:01
all
7:02
this
7:02
stuff.
7:02
So
7:02
the
7:02
only
7:03
area
7:03
we
7:03
use
7:04
AI
7:04
is
7:04
in
7:04
this
7:04
little
7:05
small
7:05
innovation
7:06
sandbox
7:07
area
7:07
that's
7:08
tightly
7:08
wrapped
7:08
and
7:09
also
7:09
doesn't
7:09
get
7:10
access
7:10
to
7:10
the
7:10
company
7:11
data.
7:12
And
7:13
you
7:13
realize,
7:13
yeah,
7:14
that's,
7:14
that's
7:14
the
7:14
reality
7:15
and
7:15
it's
7:15
going
7:15
to
7:15
be
7:15
the
7:15
reality
7:16
for
7:16
all
7:16
this
7:16
time.
7:16
So
7:17
all
7:17
these
7:17
companies
7:17
are
7:17
getting
7:18
huge
7:18
amounts
7:18
of
7:18
funding
7:19
to
7:19
do
7:19
this
7:20
build
7:20
these
7:20
AI
7:20
models,
7:21
their
7:21
customer
7:22
base
7:23
will
7:24
mostly
7:24
be
7:24
startups
7:25
or
7:25
small,
7:25
small
7:25
scale
7:26
companies
7:26
until
7:27
they
7:27
can
7:27
really
7:28
prove
7:28
out
7:28
their
7:29
security
7:29
and
7:29
all
7:30
this
7:30
other
7:30
stuff
7:30
and
7:30
make
7:31
it
7:31
tangible
7:31
for
7:32
all
7:32
these
7:32
organizations.
7:33
And
7:34
then
7:34
you
7:34
get
7:34
a
7:34
lot
7:34
of
7:34
organizations
7:35
not
7:36
even
7:36
allowing
7:37
like
7:37
cloud
7:37
or
7:38
chatgpt
7:38
to
7:39
be
7:39
used
7:39
on
7:39
their
7:39
laptops
7:40
because
7:40
of
7:41
security
7:41
risk.
7:42
It's
7:42
definitely
7:42
a
7:43
difference
7:43
between
7:44
the
7:44
reality
7:44
and
7:45
what
7:45
people
7:46
talk
7:46
about
7:46
on
7:47
things
7:47
like
7:47
LinkedIn
7:48
or
7:49
on
7:49
the
7:49
Internet
7:49
and
7:50
the
7:50
hype
7:50
out
7:50
there.
7:51
It
7:51
really
7:51
is
7:51
such
7:52
a
7:52
divergence
7:53
and
7:53
we
7:53
really
7:53
have
7:54
to
7:54
keep
7:54
that
7:54
in
7:54
mind
7:54
as
7:55
we
7:55
do
7:56
things
7:56
and
7:56
as.
7:56
We
7:56
move
7:56
forward,
7:57
I
7:57
think
7:57
there's
7:58
a
7:58
spot
7:58
where
7:58
it
7:58
belongs.
7:58
And
7:59
you
7:59
know,
7:59
if
7:59
I
7:59
was
8:01
out
8:01
of
8:01
college
8:02
and
8:02
trying
8:02
to
8:02
bootstrap
8:02
my
8:03
first
8:03
ever
8:03
SaaS
8:03
platform
8:04
and
8:04
I'd,
8:04
you
8:05
know,
8:05
done
8:05
the
8:05
hard
8:05
work,
8:05
I'd
8:06
built
8:06
a
8:06
bit
8:06
of
8:06
an
8:06
audience,
8:07
like
8:07
I
8:07
built
8:07
a
8:07
bit
8:07
of
8:07
community
8:08
around
8:08
a
8:08
problem
8:09
and
8:09
I
8:09
wanted
8:10
to
8:10
bootstrap
8:10
a
8:11
SaaS
8:11
platform,
8:11
one
8:12
of
8:12
those
8:12
overnight
8:12
success
8:12
ones
8:13
that
8:13
you
8:13
see,
8:13
like
8:13
I
8:14
saw
8:14
a
8:14
joke
8:14
the
8:14
other
8:14
day
8:14
of
8:15
like
8:16
I'm
8:16
22
8:17
and
8:17
I
8:17
built
8:18
a
8:18
9
8:18
million
8:19
monthly
8:20
revenue
8:20
platform
8:21
for,
8:21
to
8:22
teach
8:22
dolphins
8:22
how
8:22
to
8:22
code.
8:23
Ask
8:23
me
8:23
anything.
8:24
The
8:25
I
8:25
read
8:25
a
8:25
joke
8:26
about
8:26
that.
8:26
But
8:26
you
8:26
know,
8:26
joking
8:27
apart,
8:27
like
8:28
in
8:28
the
8:28
early
8:28
stage
8:28
when
8:29
you're
8:29
trying
8:29
to
8:29
prototype
8:30
and
8:30
find
8:30
product,
8:31
market
8:31
fit
8:31
and
8:32
build
8:32
something
8:32
up
8:32
to
8:32
test
8:33
it,
8:33
like
8:33
these
8:33
tools
8:34
are
8:34
allowing
8:35
for
8:35
incredible
8:35
advances
8:36
and
8:36
for
8:36
people
8:36
to
8:37
get
8:37
a
8:38
foothold
8:38
on
8:38
the
8:38
market,
8:39
which
8:39
I
8:39
think
8:40
if
8:40
it
8:40
proves
8:40
to
8:41
be
8:41
a
8:41
long
8:41
standing
8:42
kind
8:42
of
8:42
enterprise
8:43
scale
8:43
problem
8:43
that
8:43
you
8:43
want
8:43
to
8:44
fit,
8:44
you
8:44
can
8:44
put
8:44
the
8:44
proper
8:44
architecture
8:45
around
8:45
it
8:46
at
8:47
some
8:47
point
8:48
afterwards.
8:48
As
8:48
long
8:48
as
8:49
you're
8:49
not,
8:49
you
8:49
know,
8:49
running
8:49
financial
8:50
information
8:50
or
8:51
anything
8:51
that's
8:52
highly
8:52
regulated
8:52
through
8:52
there.
8:53
That's
8:54
one
8:54
point
8:54
I'd
8:54
make
8:54
about
8:55
it.
8:55
A
8:55
counterpoint
8:55
on
8:56
the,
8:56
the
8:56
GPT
8:57
and
8:57
Claude
8:57
in
8:58
corporate
8:59
environments,
8:59
I,
9:00
that's
9:00
two
9:01
things
9:01
that
9:01
concern
9:01
me
9:01
about
9:02
this.
9:02
One
9:03
is
9:03
the,
9:03
there's
9:04
a
9:04
bit
9:04
of
9:04
baby
9:04
and
9:04
bathwater
9:05
going
9:05
on
9:05
because
9:06
the
9:06
risk
9:06
we're
9:07
protecting
9:07
against
9:08
is
9:08
confidential
9:09
data,
9:09
be
9:09
it
9:10
like
9:10
personally
9:10
identified
9:11
and
9:11
personally
9:11
identifiable
9:12
information
9:12
of
9:13
our
9:13
customers
9:13
or
9:13
anything
9:14
that's,
9:14
you
9:15
know,
9:15
kind
9:15
of
9:15
confidential
9:16
or
9:16
crucial
9:17
to
9:17
the,
9:17
to
9:18
the,
9:19
the
9:19
company's
9:19
intellectual
9:20
property
9:20
of
9:21
course,
9:21
shouldn't
9:21
be
9:21
anywhere
9:22
near.
9:22
However,
9:23
when
9:23
it
9:23
comes
9:23
to
9:23
marketing
9:24
and
9:24
brand,
9:24
the
9:25
risk
9:25
we're
9:25
mitigating
9:26
against
9:26
is,
9:26
oh,
9:27
I
9:27
discuss
9:28
something
9:29
with
9:29
Claude
9:30
or
9:30
GPT
9:30
and
9:30
it
9:30
becomes
9:31
part
9:31
of
9:31
this
9:31
big
9:32
AI
9:32
brain
9:32
and
9:33
part
9:33
of
9:33
its
9:33
knowledge.
9:34
Now
9:34
if
9:34
I'm
9:34
in
9:34
marketing,
9:35
all
9:35
I'm
9:35
doing
9:35
all
9:36
day
9:36
is
9:36
talking
9:36
about
9:36
how
9:37
great
9:37
my
9:37
products
9:37
are,
9:37
how
9:38
Great.
9:38
My
9:38
company
9:38
is
9:39
what
9:39
a
9:39
good
9:39
place
9:39
this
9:39
is
9:40
to
9:40
work,
9:40
how
9:41
the
9:41
things
9:41
we
9:42
do
9:42
can
9:42
change
9:42
your
9:42
lives.
9:43
Like,
9:43
don't
9:43
you
9:44
want
9:44
that
9:44
in
9:44
there?
9:44
Yeah,
9:45
I
9:45
think
9:45
it's
9:45
about
9:45
kind
9:45
of
9:46
realizing
9:46
what
9:46
you
9:47
need
9:47
it
9:47
for
9:47
and
9:47
how
9:47
to
9:48
use
9:48
it
9:48
and
9:48
such
9:48
like
9:49
that.
9:49
And
9:49
I
9:50
think
9:50
you're
9:50
right.
9:50
For
9:51
a
9:51
small
9:51
organization,
9:52
it's
9:52
just
9:53
so
9:53
key,
9:53
especially
9:54
on
9:54
doing
9:54
certain
9:55
tasks.
9:55
I
9:55
mean,
9:56
you
9:56
spoke
9:56
about
9:57
my
9:57
newsletter.
9:57
I,
9:58
I
9:58
use
9:58
cloud
9:59
a
9:59
lot
9:59
for
9:59
my
9:59
newsletter
10:00
and
10:00
a
10:00
lot
10:00
for
10:00
writing.
10:01
And
10:01
I
10:01
think
10:01
it's,
10:01
it's
10:01
accelerated
10:02
my
10:02
ability
10:03
to,
10:03
to
10:03
write
10:04
these
10:04
newsletters
10:04
and
10:05
do
10:05
things.
10:05
Especially
10:05
because
10:06
a
10:06
lot
10:06
of
10:06
what
10:06
I
10:07
write
10:07
out
10:07
is
10:08
outside
10:08
of
10:09
my
10:10
initial
10:10
domain
10:11
of
10:11
expertise.
10:11
I'm
10:11
trying
10:12
to
10:12
explore
10:13
and
10:13
explain
10:13
the
10:14
entire
10:14
data
10:14
ecosystem.
10:16
I'm
10:16
not
10:16
a
10:16
data
10:16
engineer,
10:17
I'm
10:17
not
10:17
a
10:17
machine
10:18
learning
10:18
scientist.
10:19
I
10:19
can
10:20
do
10:20
a
10:20
ton
10:20
of
10:20
research
10:20
and
10:20
write
10:21
about
10:21
this
10:21
stuff.
10:21
AI
10:22
helps
10:22
me
10:22
do
10:23
that.
10:23
I
10:24
have
10:24
to
10:24
do
10:25
a
10:25
ton
10:25
of
10:25
editing
10:26
and
10:26
I
10:26
have
10:26
to
10:26
do
10:27
a
10:27
ton
10:27
of
10:27
kind
10:27
of
10:28
source
10:28
checking
10:29
and
10:29
research
10:29
and
10:29
stuff
10:30
just
10:30
to
10:30
make
10:30
sure
10:30
it
10:30
actually
10:31
lands.
10:31
Because
10:32
AI
10:33
is
10:33
not
10:33
thinking
10:34
about
10:34
this
10:35
in
10:36
a
10:36
more
10:36
complex
10:36
or
10:37
critical
10:37
way.
10:39
But
10:39
it
10:39
does
10:40
help
10:40
me
10:40
kind
10:41
of
10:41
set
10:41
that
10:42
benchmark
10:42
that
10:43
then
10:43
I
10:43
can
10:43
write
10:43
out
10:44
and
10:44
build
10:44
on.
10:44
And
10:44
I
10:44
think
10:45
companies
10:46
need
10:47
to
10:47
learn
10:47
how
10:47
to
10:48
do
10:48
that
10:48
internally
10:50
because
10:50
you
10:50
get
10:50
two
10:51
different
10:52
parts
10:53
of
10:53
the
10:53
coin.
10:53
Sometimes
10:54
they
10:54
just
10:54
kind
10:54
of
10:54
take
10:54
blindly
10:55
what
10:56
AI
10:56
gives
10:56
them
10:58
and
10:58
it's
10:58
not
10:59
nearly
10:59
good
11:00
enough.
11:00
And
11:00
you
11:01
see
11:01
that
11:01
with
11:01
some
11:02
recent
11:02
studies
11:02
out
11:02
there
11:02
as
11:03
well.
11:04
And
11:04
then
11:04
on
11:05
the
11:05
other
11:05
hand,
11:05
they
11:05
just
11:05
kind
11:06
of
11:06
don't
11:07
use
11:07
AI
11:07
at
11:07
all
11:08
and
11:09
are
11:09
missing
11:09
out
11:10
on
11:10
all
11:10
these
11:10
efficiency
11:11
gains.
11:11
So
11:12
it
11:12
really
11:12
is
11:12
about
11:13
kind
11:13
of
11:14
knowing
11:14
how
11:14
and
11:14
when
11:15
to
11:15
use
11:15
it
11:15
and
11:16
what
11:16
to
11:17
use
11:17
as
11:17
well.
11:17
Yeah,
11:18
you
11:18
talked
11:18
about
11:18
your
11:19
newsletters,
11:19
which
11:19
I
11:20
love,
11:20
and
11:20
I'm
11:20
a
11:21
big
11:21
fan
11:21
of
11:21
your
11:21
LinkedIn
11:22
content
11:22
as
11:22
well.
11:23
One
11:23
of
11:23
the
11:23
things
11:23
I
11:24
like
11:24
the
11:24
most
11:24
about
11:24
it
11:24
is
11:25
the
11:25
diagrams
11:25
that
11:25
you
11:26
put
11:26
together
11:26
that
11:26
take
11:26
really
11:27
complex,
11:29
wide
11:29
ranging
11:29
issues
11:30
or
11:30
platforms
11:31
or
11:31
capabilities
11:31
and
11:32
put
11:32
them
11:32
into
11:32
this
11:33
digestible,
11:33
kind
11:34
of
11:34
easy
11:34
to
11:34
understand,
11:35
nice
11:35
pastel
11:35
colored
11:36
format.
11:37
Are
11:37
you
11:37
using
11:38
any
11:38
tools
11:39
for
11:39
that?
11:39
I
11:39
mean,
11:39
I
11:39
found
11:40
the
11:40
LLMs
11:41
are
11:41
generally
11:42
pretty
11:42
hopeless
11:42
at
11:42
putting
11:43
diagrams
11:43
together.
11:45
How
11:45
are
11:46
you
11:46
putting
11:46
that
11:46
together?
11:46
Are
11:47
you
11:47
crafting
11:47
it
11:47
by
11:48
hand
11:48
with
11:48
colored
11:48
pencils?
11:51
No,
11:52
I
11:52
don't
11:52
think
11:52
I
11:52
have.
11:53
I
11:53
don't
11:53
think
11:53
I
11:53
have
11:53
that
11:54
skill
11:54
set
11:54
with
11:54
drawing
11:55
anymore.
11:55
So
11:55
I
11:55
don't
11:55
think
11:56
I
11:56
could
11:56
craft
11:56
that
11:56
by
11:57
hand.
11:58
No,
11:59
I
11:59
use
11:59
a
12:00
tool
12:00
called
12:00
ExcaliDraw.
12:02
It's
12:02
actually
12:02
the
12:02
most
12:03
asked
12:03
question
12:03
I
12:04
get
12:04
on
12:04
the
12:04
comments
12:04
of
12:05
my
12:05
newsletter.
12:06
And
12:06
on
12:06
my
12:06
LinkedIn
12:07
messages.
12:08
So
12:08
Xcelidraw,
12:09
if
12:09
you
12:09
wanna
12:09
sponsor
12:10
me,
12:10
I
12:10
can
12:10
spread
12:10
it
12:11
the
12:11
word
12:11
even
12:11
more.
12:12
But
12:13
it's,
12:14
it's
12:14
really
12:15
cool
12:15
because
12:15
it
12:15
does
12:16
bring.
12:16
It
12:17
makes
12:17
it
12:17
more
12:18
human.
12:18
Right?
12:18
And
12:19
that's
12:19
what
12:19
frameworks
12:19
are
12:19
meant
12:20
to
12:20
do.
12:20
It,
12:20
it
12:20
really
12:21
gives
12:21
you
12:21
a
12:21
visual
12:22
guide
12:23
for
12:23
a
12:24
block
12:24
text
12:24
of
12:25
information.
12:25
And
12:25
working
12:26
as
12:26
a
12:26
consultant
12:26
my
12:26
entire
12:27
career,
12:28
that's
12:28
what
12:28
we
12:28
build
12:28
for
12:28
clients.
12:29
We
12:29
build
12:29
you
12:29
a
12:30
framework
12:30
that
12:31
kind
12:31
of
12:31
explain
12:32
difficult
12:32
to
12:33
understand
12:33
concepts
12:34
or
12:34
like
12:35
strategic
12:35
concepts
12:36
in
12:36
a
12:37
manageable
12:37
way.
12:37
Like
12:37
my
12:38
favorite
12:38
one,
12:38
for
12:38
example,
12:39
is
12:40
like
12:40
a
12:40
business
12:41
strategy
12:41
temple.
12:42
I'd
12:42
always
12:42
build
12:43
a
12:43
strategy
12:43
temple
12:44
with
12:44
like
12:44
the
12:44
vision
12:44
at
12:45
the
12:45
top,
12:45
supported
12:46
by
12:46
the
12:46
pillars
12:47
of
12:47
like
12:47
your
12:47
main
12:48
initiatives
12:49
and
12:49
stuff
12:50
like
12:50
that,
12:50
and
12:50
then
12:50
underpinned
12:51
with
12:51
the
12:52
foundation
12:52
of
12:52
like
12:52
your
12:53
culture
12:53
or
12:53
whatever
12:53
that
12:54
might
12:54
be.
12:54
So
12:56
for
12:56
me,
12:56
building
12:57
these
12:57
frameworks
12:58
helps
12:59
kind
12:59
of
12:59
elucidate
13:00
some
13:00
of
13:00
these
13:01
complex
13:01
ideas
13:02
that
13:02
exist
13:02
in
13:02
data.
13:03
And
13:04
I
13:04
mean,
13:04
to
13:04
your
13:05
point,
13:05
LLMs
13:05
aren't
13:06
good
13:06
at
13:06
drawing
13:06
diagrams,
13:07
but
13:08
no
13:08
offense
13:08
to
13:09
the
13:09
data
13:09
community
13:09
is
13:10
most
13:10
data
13:10
people
13:11
aren't
13:11
either.
13:13
And
13:13
unless
13:14
it's
13:14
like
13:14
a
13:14
technical
13:15
architecture,
13:16
which
13:16
is
13:16
complex.
13:19
So
13:19
what
13:19
this,
13:20
what
13:20
I've
13:20
tried
13:20
to
13:20
do
13:20
is
13:20
just
13:21
try
13:21
to
13:21
pare
13:21
it
13:22
back.
13:22
And
13:22
I
13:22
think
13:22
that
13:22
has
13:23
been
13:23
one
13:23
of
13:23
my
13:23
differentiators.
13:24
And
13:25
I
13:25
like
13:25
doing
13:25
it.
13:26
It
13:26
does
13:26
get
13:26
hard.
13:26
I've
13:27
got
13:27
this.
13:28
You
13:28
should
13:28
see
13:28
my
13:28
excalidraw.
13:29
It's
13:29
got
13:29
like,
13:30
I
13:30
think
13:30
now
13:31
over
13:31
a
13:31
hundred
13:31
different
13:32
frameworks,
13:33
images.
13:34
I
13:35
need
13:35
to
13:35
spend
13:35
like
13:35
an
13:35
afternoon
13:36
just
13:36
cleaning
13:36
it
13:36
up,
13:37
to
13:37
be
13:37
honest.
13:37
But.
13:39
I
13:40
enjoy
13:40
building
13:40
them
13:40
because
13:42
they
13:42
are
13:43
kind
13:43
of
13:43
helping
13:43
me.
13:45
It
13:45
helps
13:45
me
13:46
even
13:46
understand
13:47
how
13:47
to
13:47
think
13:47
about
13:48
these
13:48
things
13:48
in
13:48
more
13:48
of
13:48
a
13:48
strategic
13:49
way.
13:49
You
13:49
need
13:49
to
13:49
spend
13:50
an
13:50
afternoon
13:50
tidying
13:50
them
13:50
up
13:51
and
13:51
then
13:51
turning
13:51
them
13:51
into
13:51
a
13:51
book,
13:51
Dylan.
13:52
That's
13:52
all.
13:52
I
13:52
reckon
13:54
it
13:54
might
13:54
happen.
13:55
We'll
13:55
see.
13:58
Put
13:58
me
13:58
down
13:58
for
13:58
the
13:58
pre
13:58
order.
14:00
So
14:01
excalidraw
14:01
is.
14:01
It's
14:02
about
14:02
like
14:02
Excalibur
14:03
but
14:03
with
14:03
withdraw
14:04
on
14:04
the
14:04
end.
14:04
Or
14:04
is
14:05
it.
14:05
How
14:05
do
14:05
you
14:06
spell
14:06
it
14:06
for
14:06
folks
14:06
listening
14:07
who
14:07
want
14:07
to
14:07
find
14:07
it?
14:07
I
14:08
think
14:08
it's
14:08
E,
14:08
E
14:09
X
14:09
C
14:10
A.
14:12
Yeah.
14:12
Ex
14:13
C
14:13
A
14:13
L
14:14
I
14:15
D
14:15
R-A
14:16
W
14:17
dot
14:17
com.
14:17
All
14:18
right.
14:18
Yeah,
14:18
it's
14:18
Scarlet
14:19
Draw.
14:19
If
14:19
you're
14:19
listening,
14:19
Dylan
14:20
needs
14:20
a
14:20
referral
14:21
code
14:21
fast.
14:23
I'll
14:23
put
14:23
my
14:23
first
14:24
name.
14:24
I'll
14:24
put
14:24
my
14:24
name
14:24
down
14:25
for
14:25
that
14:25
too.
14:25
But
14:26
those
14:26
diagrams
14:26
are
14:27
excellent.
14:27
I
14:27
have
14:27
played
14:27
a
14:27
little
14:27
bit
14:27
with
14:28
Napkin
14:28
when
14:28
Napkin
14:29
first
14:29
came
14:29
out.
14:29
Have
14:29
you
14:29
seen?
14:30
Yeah,
14:30
I
14:30
think
14:30
I've
14:31
seen
14:31
Napkin.
14:31
Yeah,
14:32
it
14:32
got
14:32
very
14:32
samey
14:33
after
14:33
a
14:33
while,
14:33
I
14:33
think
14:34
was
14:34
my
14:35
takeaway.
14:37
I
14:37
haven't
14:38
visited
14:38
it
14:38
since
14:38
and
14:38
they
14:39
may
14:39
have
14:39
introduced
14:40
new
14:40
formats
14:40
or
14:40
whatever
14:40
else,
14:41
but
14:42
this
14:43
is
14:43
part
14:43
of
14:43
the
14:44
going
14:44
back
14:44
to
14:44
the
14:44
SaaS
14:45
platforms
14:45
that
14:45
we
14:45
talked
14:45
about.
14:46
I'm
14:46
sure
14:46
Exkelidraw
14:47
is
14:47
one
14:47
of
14:47
those,
14:47
right.
14:48
That
14:48
was
14:48
kind
14:48
of
14:48
built
14:49
on
14:49
early
14:49
stage
14:50
AI
14:50
architecture,
14:51
kind
14:51
of
14:51
blew
14:51
up,
14:51
found
14:51
a
14:51
product
14:52
market
14:52
fit
14:53
and
14:54
these
14:54
tools
14:54
have
14:55
such
14:55
flexibility
14:56
and
14:56
the,
14:58
the
14:58
cost
14:58
of
14:58
entry
14:58
into
14:59
the
14:59
market
14:59
has
14:59
got
15:00
so
15:00
much
15:00
lower
15:00
in
15:00
terms
15:00
of
15:01
both
15:02
actual
15:02
cost
15:02
in
15:02
dollars
15:03
as
15:03
well
15:03
as
15:04
technical
15:04
skill
15:04
required.
15:06
So
15:07
that's
15:08
why
15:08
I
15:08
always
15:08
ask
15:08
folks
15:08
about
15:09
their
15:09
favorite
15:09
AI
15:09
tools.
15:10
Because
15:10
everyone's
15:10
got
15:10
something
15:10
different,
15:11
right?
15:11
Because
15:11
there's
15:12
so
15:12
many,
15:12
there
15:12
are
15:13
so
15:13
many
15:13
to
15:13
choose
15:13
from.
15:14
Are
15:14
there
15:14
any
15:14
others
15:14
other
15:15
than
15:15
excalidraw
15:16
that
15:16
are
15:16
favorites
15:16
of
15:16
yours?
15:17
Well,
15:17
excalidraw
15:18
is
15:18
not
15:18
AI.
15:18
It
15:18
does
15:18
have
15:19
AI
15:19
powered
15:19
stuff
15:20
to
15:20
create
15:20
diagrams,
15:21
but
15:21
I
15:21
don't
15:21
use
15:21
it
15:22
because
15:22
it's.
15:22
It
15:22
doesn't
15:23
deliver
15:23
the
15:23
diagrams
15:24
to
15:24
the
15:24
quality
15:25
that
15:25
I
15:25
want.
15:26
The
15:26
AI
15:27
ones
15:27
that
15:27
I
15:27
use
15:28
are.
15:28
It's
15:29
pretty
15:29
much
15:29
Claude.
15:30
I
15:30
pretty
15:31
much
15:31
use
15:31
cloud
15:31
just
15:32
for
15:32
writing
15:32
and
15:33
I
15:33
think
15:33
the
15:33
ability
15:34
to
15:34
upload
15:34
your
15:34
own
15:35
material.
15:35
So
15:36
now
15:36
it
15:36
kind
15:36
of
15:36
even
15:37
has
15:37
its
15:37
own
15:38
MCP
15:38
type
15:39
thing
15:39
rag
15:39
model
15:40
embedded
15:41
in
15:41
it.
15:41
Right.
15:41
Because
15:42
it's
15:42
got.
15:42
Okay,
15:43
this
15:43
is
15:43
my
15:43
writing
15:44
style
15:44
and
15:44
Now
15:44
I've
15:45
written
15:45
45
15:46
different
15:46
newsletters
15:47
articles
15:48
so
15:48
it
15:48
can
15:48
actually
15:49
see
15:49
these
15:49
are
15:49
my
15:49
best
15:50
ones.
15:50
This
15:50
is,
15:51
I
15:51
have
15:51
like
15:51
them
15:52
grouped
15:52
as
15:52
well.
15:52
Like
15:53
these
15:53
are
15:53
my
15:53
data
15:53
quality
15:54
ones.
15:54
These
15:54
are
15:54
my
15:54
kind
15:54
of
15:55
architecture
15:55
and
15:55
engineering
15:56
ones.
15:56
So
15:56
it
15:57
gets
15:57
to
15:57
know
15:57
and
15:57
understand
15:58
how
15:58
I
15:58
think
15:59
about
15:59
these
15:59
topics.
16:00
So
16:01
that
16:01
has
16:01
helped
16:02
a
16:02
lot
16:03
because
16:03
it
16:03
learns
16:04
from
16:05
what
16:05
I've
16:05
created.
16:07
So
16:07
yeah,
16:07
that,
16:08
that
16:08
and
16:08
I
16:09
guess
16:09
the
16:09
other
16:09
one
16:09
is
16:09
a
16:10
Grammarly.
16:11
Grammarly
16:11
is
16:11
great
16:12
for
16:12
just
16:12
like
16:12
catching
16:13
mistakes
16:14
that
16:14
you're
16:15
going
16:15
to
16:15
inevitably
16:16
make.
16:17
Yeah,
16:17
no.
16:18
Big
16:18
fan
16:18
of
16:18
Grammarly
16:19
as
16:19
well.
16:19
Although
16:21
I
16:21
think
16:22
when
16:22
I
16:22
first
16:22
got
16:22
it,
16:22
I
16:22
clicked
16:23
yes
16:23
on
16:23
everything
16:23
and
16:24
found
16:24
that
16:24
it
16:24
just
16:25
sucked
16:25
the
16:25
soul
16:25
and
16:25
my
16:26
personality
16:26
out
16:26
of
16:26
all
16:27
of
16:27
my
16:27
writing.
16:27
So
16:29
it's
16:30
used
16:30
with
16:30
caution.
16:32
So
16:32
in
16:32
effect
16:33
the
16:34
LLM
16:34
becomes
16:34
a
16:34
bit
16:34
of
16:35
a
16:35
data
16:35
set
16:35
for
16:35
you.
16:35
Right.
16:36
So
16:36
it
16:36
has
16:36
45
16:36
pieces
16:37
of
16:37
your
16:38
writing
16:39
and
16:39
then
16:39
you
16:39
hinted
16:40
at
16:40
this,
16:40
but
16:40
I
16:40
just
16:40
want
16:40
to
16:41
check
16:41
in.
16:41
Do
16:41
you
16:41
then
16:42
feed
16:42
in
16:42
context
16:43
back
16:43
in
16:43
of
16:44
how
16:44
well
16:44
each
16:44
one
16:44
has
16:45
done
16:45
or
16:45
have
16:45
something
16:46
set
16:46
up
16:46
to
16:46
monitor
16:46
that
16:47
so
16:47
that
16:47
it
16:47
knows
16:48
which
16:48
one's
16:48
hit
16:48
and
16:49
which
16:49
one's
16:49
less
16:50
so.
16:50
Yeah,
16:50
so
16:51
I
16:51
actually
16:51
don't
16:51
upload
16:52
all
16:52
of
16:52
them.
16:52
I
16:52
upload
16:53
My,
16:53
my
16:53
top
16:54
performing
16:54
ones
16:54
and
16:54
the
16:55
ones
16:55
that
16:55
I
16:55
felt
16:56
I
16:56
wrote
16:56
really
16:56
well
16:57
on.
16:58
And
16:58
so
16:58
it
16:58
only
16:59
pulls
16:59
from
16:59
probably
17:00
about
17:01
15
17:01
to
17:02
20
17:02
and
17:02
then
17:02
I
17:02
do
17:03
have
17:03
those
17:03
kind
17:03
of
17:04
context
17:04
driven
17:05
groupings
17:06
as
17:06
well
17:06
depending
17:07
on.
17:07
So
17:08
this
17:08
chat
17:08
I'll
17:08
add
17:09
my
17:09
data
17:09
equality
17:10
ones
17:10
because
17:10
I'm
17:10
writing
17:10
a
17:10
bunch
17:10
of
17:11
data
17:11
quality
17:11
articles
17:12
or
17:12
whatever
17:13
it
17:13
might
17:13
be.
17:14
So
17:14
that
17:15
does,
17:15
does
17:15
help
17:16
a
17:16
lot.
17:17
But
17:18
and
17:18
then,
17:19
I
17:19
mean
17:19
now
17:20
with
17:21
its
17:21
ability
17:22
to
17:22
reach
17:22
the
17:22
Internet
17:23
and
17:23
everything,
17:23
it
17:23
does
17:24
kind
17:24
of
17:24
you
17:25
can
17:25
give
17:25
it,
17:25
oh,
17:26
I
17:26
really
17:26
like
17:26
this
17:27
person's
17:27
blog
17:28
or
17:28
this
17:29
person's
17:29
substack.
17:30
Please
17:30
draw
17:31
from
17:32
some
17:32
of
17:32
their
17:32
work
17:33
because
17:33
to
17:33
be
17:34
honest,
17:34
if
17:34
you
17:34
leave
17:35
the
17:35
LLM
17:35
on
17:35
its
17:35
own,
17:36
especially
17:37
like
17:37
a
17:37
GBT
17:38
or
17:38
cloud
17:38
or
17:39
whatever,
17:40
it
17:40
just
17:40
gets
17:40
the
17:40
first
17:41
things
17:41
that
17:41
come
17:41
up
17:41
on
17:42
the
17:42
Internet
17:42
and
17:42
it's
17:42
super
17:42
generic
17:44
crap
17:45
that's
17:45
written
17:45
by
17:46
like,
17:46
you
17:46
know,
17:47
I'm
17:47
not
17:47
going
17:47
to
17:47
name
17:47
names,
17:48
but
17:49
you
17:50
can
17:50
tell
17:50
that
17:50
the
17:50
stuff,
17:52
yeah,
17:53
you
17:53
could
17:53
tell
17:53
even
17:53
the
17:53
stuff
17:54
that
17:54
pulls
17:54
from
17:54
is
17:54
probably
17:55
written
17:55
by
17:55
AI.
17:56
So
17:56
you
17:56
really
17:57
kind
17:57
of
17:57
have
17:57
to
17:57
be
17:57
a
17:57
bit
17:58
selective
17:58
of
17:58
what
17:58
you're
17:59
pulling
17:59
from
17:59
and
17:59
be
17:59
like,
18:00
okay,
18:00
I
18:00
actually
18:00
want
18:00
something
18:01
from
18:01
this
18:02
person.
18:02
So
18:02
for
18:02
example,
18:02
right
18:03
now
18:03
I'm
18:03
writing
18:03
on
18:03
data
18:04
governance
18:05
and
18:05
I
18:06
really
18:06
like
18:07
the
18:07
Data
18:08
Governance
18:08
Playbook,
18:08
which
18:09
is
18:09
a,
18:09
a
18:09
substack
18:10
by
18:11
Charlotte
18:12
Lidot.
18:13
And
18:13
I
18:13
also
18:14
know
18:14
that
18:14
like
18:14
Nicola
18:15
Askam
18:16
writes
18:16
really
18:16
good
18:16
stuff
18:17
on,
18:17
on
18:17
data
18:17
governance.
18:18
So
18:18
I've
18:18
kind
18:18
of
18:18
been
18:18
pulling,
18:19
like
18:20
pull
18:20
from
18:20
their
18:21
stuff
18:21
and
18:21
give
18:22
me
18:22
some
18:22
of
18:22
their
18:22
kind
18:23
of
18:23
findings
18:23
because
18:24
they're
18:24
really
18:24
good.
18:25
So
18:26
if
18:26
you
18:26
can
18:27
kind
18:27
of
18:27
give
18:27
it
18:27
more
18:27
instructions
18:28
in
18:28
that
18:28
way,
18:28
it
18:28
does
18:29
help
18:29
you
18:29
kind
18:29
of
18:29
corner
18:30
down
18:30
the
18:30
market
18:30
and
18:31
saves
18:31
you
18:31
a
18:31
ton
18:31
of
18:31
time
18:31
on
18:32
research.
18:33
It's
18:33
almost
18:34
like
18:34
you're
18:34
investing
18:35
in
18:35
a
18:36
high
18:36
quality
18:37
curated
18:38
data
18:38
set
18:38
for
18:38
it
18:38
to
18:39
operate
18:39
from.
18:39
What
18:40
a
18:40
novel
18:40
idea.
18:40
It
18:40
might
18:40
catch
18:41
on.
18:41
It
18:41
might
18:41
catch
18:42
on.
18:43
I
18:43
want
18:44
to
18:44
come
18:44
back
18:44
to
18:44
the
18:44
temple
18:44
that
18:45
you
18:45
talked
18:45
about.
18:45
The
18:46
temple
18:46
diagrams
18:47
where
18:47
you
18:47
have
18:47
the
18:47
business
18:47
strategy
18:48
and
18:48
the
18:48
data
18:48
in
18:49
the
18:49
middle
18:50
and
18:50
the
18:50
culture
18:51
at
18:51
the
18:51
bottom.
18:53
Supercritical
18:54
point.
18:54
As
18:54
I
18:54
always
18:54
say
18:55
to
18:55
all
18:55
of
18:55
my
18:56
clients,
18:56
data
18:57
and
18:57
technology,
18:58
in
18:58
whatever
18:58
form
18:59
you
18:59
want
18:59
to
18:59
say,
18:59
are
19:00
never
19:00
business
19:00
cases
19:00
in
19:01
their
19:01
own
19:01
right.
19:02
They
19:02
are
19:03
enablers
19:03
of
19:04
a
19:04
business
19:04
case.
19:04
They
19:05
are
19:05
vessels
19:06
through
19:06
which
19:06
to
19:06
deliver
19:07
a
19:07
business,
19:08
a
19:09
business
19:09
strategy.
19:10
What
19:10
do
19:10
you
19:11
do
19:11
when
19:11
you
19:11
start
19:12
to
19:12
draw
19:12
the
19:12
temple
19:13
and
19:13
you
19:13
find
19:13
out
19:13
that
19:13
the
19:13
top
19:14
of
19:14
the
19:14
temple
19:14
isn't
19:14
very
19:14
clear?
19:17
How
19:17
do
19:17
you
19:17
manage
19:17
that
19:18
interaction?
19:20
It
19:20
happens
19:21
way
19:21
too
19:21
often.
19:22
I
19:22
go
19:23
to
19:23
a
19:23
client
19:23
and
19:23
what's
19:24
your
19:24
strategy
19:25
here?
19:26
And
19:26
I'm
19:26
like
19:26
that's
19:27
not
19:27
really
19:27
a
19:27
strategy.
19:28
That's
19:28
a
19:28
couple
19:29
KPIs
19:30
at
19:30
best.
19:31
And
19:33
so
19:33
I,
19:34
I
19:34
usually
19:34
actually
19:34
even
19:35
include
19:35
that
19:35
in
19:35
a
19:36
lot
19:36
of
19:36
my
19:36
work
19:36
is
19:36
like,
19:37
okay,
19:37
I
19:37
know
19:37
we're
19:37
going
19:37
to
19:38
be
19:38
kind
19:38
of
19:38
re.
19:38
Rejigging,
19:39
re
19:39
looking
19:40
at
19:40
your
19:40
strategy
19:41
a
19:41
bit
19:41
and
19:41
figuring
19:42
out
19:42
how
19:42
data
19:42
kind
19:43
of
19:43
supports
19:43
it.
19:44
Luckily
19:45
my
19:45
background
19:46
is
19:46
strategy
19:46
consulting
19:47
as
19:47
well.
19:48
So
19:48
I
19:48
have
19:48
that
19:48
kind
19:48
of
19:48
business
19:49
sense
19:49
and
19:49
that
19:50
business
19:50
background
19:50
and,
19:51
and
19:51
it's
19:51
honestly
19:52
just
19:52
kind
19:52
of
19:52
talking,
19:52
working
19:53
with
19:53
stakeholders
19:53
be
19:53
like,
19:54
hey,
19:54
what
19:54
do
19:54
you
19:54
do?
19:55
Like,
19:55
how
19:55
does
19:55
your
19:55
organization
19:56
make
19:56
money?
19:56
If
19:57
you're
19:57
a
19:57
private
19:58
organization
19:58
or
19:58
if
19:58
you're
19:59
a
19:59
public
19:59
organization,
19:59
how
20:00
do
20:00
you
20:00
deliver
20:00
value
20:00
to
20:01
your
20:01
stakeholders?
20:02
Yeah,
20:03
and,
20:04
and
20:04
then
20:05
you
20:05
kind
20:05
of
20:05
talk
20:05
through
20:05
it,
20:06
you,
20:06
you
20:06
diagram
20:07
it
20:07
out.
20:07
I,
20:08
I
20:08
have
20:08
an
20:08
example
20:08
of
20:09
one
20:09
client
20:10
that
20:10
I
20:11
worked
20:11
with
20:11
where
20:12
I
20:12
completely
20:13
kind
20:13
of,
20:14
me
20:14
and
20:14
my
20:14
team,
20:14
we,
20:15
we
20:15
built
20:16
their
20:16
business
20:16
model
20:17
on
20:17
a
20:17
page
20:17
and
20:18
we
20:18
built
20:18
it
20:18
with
20:19
a
20:19
data
20:19
perspective
20:19
on
20:20
it.
20:20
And
20:20
they're
20:20
like,
20:20
wow,
20:20
this
20:20
is
20:21
better
20:21
than
20:21
like
20:21
how
20:22
we
20:22
understand
20:22
our
20:22
business
20:23
model.
20:23
We're
20:23
going
20:23
to
20:23
start
20:24
using
20:24
this
20:24
internally
20:25
even
20:25
for
20:25
not
20:25
data
20:26
resources
20:26
reasons.
20:27
And
20:28
then
20:28
I
20:28
was
20:28
like,
20:28
okay,
20:29
then
20:29
this
20:29
is
20:29
how
20:29
data
20:30
supports
20:30
you
20:30
because
20:30
you're
20:31
more
20:31
of
20:31
a
20:31
data
20:31
enabled
20:32
company
20:32
because
20:32
you're,
20:32
you're
20:33
in
20:33
marketing
20:33
and
20:34
to
20:34
be
20:34
good
20:34
at
20:34
marketing
20:35
you
20:35
need
20:35
data
20:35
to
20:36
make
20:37
better
20:37
decisions
20:37
and
20:37
better
20:37
understand
20:38
your
20:38
customers
20:38
and
20:39
your
20:39
audience
20:39
and
20:40
stuff
20:40
like
20:40
that.
20:41
And
20:42
that
20:42
kind
20:43
of,
20:43
that
20:45
parallels.
20:46
So
20:46
it
20:46
pulls
20:47
from
20:47
the
20:47
business
20:47
strategy
20:48
and
20:48
then
20:48
pulls
20:49
down
20:49
kind
20:49
of
20:50
why
20:50
data
20:51
is
20:51
important
20:51
to
20:52
enable
20:52
that
20:52
business
20:52
strategy.
20:53
And
20:54
once
20:54
you
20:54
start,
20:54
kind
20:54
of
20:54
see
20:55
that
20:55
like
20:55
people
20:55
on
20:56
board,
20:56
people
20:56
on
20:57
all
20:57
teams
20:57
get
20:58
it
20:58
right
20:58
and
20:58
that's,
20:58
you
20:59
kind
20:59
of
20:59
work
20:59
that
20:59
in
21:00
that,
21:00
that
21:00
change
21:00
management,
21:01
that
21:01
buy
21:01
in
21:01
and
21:02
you're
21:02
like,
21:03
okay,
21:03
this
21:03
is
21:03
how
21:03
data
21:04
supports
21:04
it
21:04
all.
21:05
And
21:05
then
21:05
you
21:05
kind
21:05
of
21:05
get
21:06
to,
21:06
okay,
21:06
now
21:06
that
21:06
we
21:07
know
21:07
what
21:07
we're
21:07
trying
21:07
to
21:07
achieve,
21:08
now
21:08
that
21:09
we
21:09
know
21:09
kind
21:09
of
21:10
how
21:10
data
21:11
might
21:11
help
21:11
us
21:11
achieve
21:12
that,
21:12
what
21:12
do
21:13
we
21:13
actually
21:13
do?
21:13
And
21:14
then
21:14
you
21:14
get
21:14
into
21:14
the
21:14
use
21:15
case,
21:15
then
21:15
you
21:15
get
21:15
into
21:15
like
21:16
we're
21:16
going
21:16
to
21:16
build
21:16
this
21:17
dashboard
21:18
or
21:18
this
21:18
AI
21:19
tool
21:19
or
21:19
even
21:20
kind
21:20
of
21:20
set
21:20
up
21:20
these
21:21
foundations
21:21
to
21:22
support
21:22
those
21:22
things.
21:23
And
21:23
that's
21:23
kind
21:23
of
21:23
where
21:24
it
21:24
becomes
21:24
a
21:25
lot
21:25
more
21:25
clear.
21:26
And
21:26
I
21:26
think
21:27
90%
21:28
of
21:28
the
21:28
companies
21:29
out
21:29
there
21:29
are
21:29
missing
21:29
that
21:30
because
21:30
they
21:31
don't.
21:31
They
21:31
build
21:32
for,
21:33
they
21:33
build
21:33
to
21:33
build
21:34
and
21:34
they
21:34
build
21:35
just
21:35
for
21:35
the
21:35
sake
21:35
of
21:36
it.
21:36
And
21:37
even
21:37
like
21:39
I've
21:39
worked
21:39
with
21:40
lots
21:40
of
21:40
data
21:40
analysts
21:40
and
21:41
data
21:41
scientists
21:41
and
21:42
a
21:42
lot
21:42
of
21:42
them
21:42
are
21:42
very
21:42
smart,
21:43
really
21:43
good
21:43
individuals,
21:44
but
21:45
they
21:45
can't
21:45
necessarily
21:46
see
21:46
that
21:46
because
21:46
they
21:47
never
21:47
actually
21:47
get
21:47
the
21:47
context
21:48
of
21:48
the
21:48
business
21:49
strategy
21:49
and
21:49
they
21:49
never
21:50
understand
21:51
how
21:51
data
21:52
supports
21:52
that
21:53
and
21:53
what
21:53
the
21:53
kind
21:53
of
21:53
through
21:53
line
21:54
is.
21:54
Yeah.
21:55
That
21:55
makes
21:55
it
21:55
harder
21:55
for
21:55
them
21:56
to
21:56
unleash
21:56
their
21:56
brilliance.
21:57
Right.
21:57
For
21:57
the
21:57
benefit
21:57
of
21:58
the
21:58
company
21:58
that
21:59
they
21:59
are
22:00
supporting
22:00
in
22:00
that
22:00
moment.
22:01
And
22:02
I've
22:02
had
22:02
very
22:03
similar
22:03
experiences
22:05
to
22:05
yours
22:05
as
22:06
well.
22:06
Like
22:06
I
22:07
often
22:07
have
22:07
a
22:07
joke
22:07
that
22:10
first
22:10
couple
22:10
of
22:10
days
22:11
with
22:11
a
22:11
client
22:11
and
22:12
you
22:12
get
22:12
the
22:12
question
22:12
like,
22:12
what
22:13
bi
22:13
tool
22:13
are
22:13
we
22:13
going
22:13
to
22:13
use?
22:14
And
22:14
I'm
22:14
like,
22:14
oh,
22:15
but
22:15
so
22:15
we've
22:16
only
22:16
just
22:16
met.
22:19
It's
22:19
very
22:19
forward
22:20
of
22:20
you.
22:20
Save
22:21
it
22:21
for
22:21
the
22:21
third
22:21
date.
22:22
Yeah,
22:23
very
22:23
forward
22:23
of
22:23
you.
22:24
And
22:24
right
22:24
now
22:25
it
22:25
doesn't
22:25
matter.
22:25
Right.
22:25
For
22:26
all
22:26
the
22:26
reasons
22:26
that
22:26
you
22:27
that,
22:27
that
22:27
you
22:27
talked
22:28
about.
22:28
It's.
22:29
And
22:29
you
22:29
know,
22:30
Dylan,
22:30
is
22:30
why
22:30
we've
22:31
had
22:31
good
22:31
conversations
22:31
before.
22:31
You
22:32
and
22:32
I
22:32
have
22:32
similar
22:32
backgrounds
22:33
and
22:34
the
22:35
same
22:35
as
22:35
you.
22:35
I
22:35
enjoy
22:36
the
22:36
opportunity
22:36
to
22:36
go
22:37
in
22:37
and,
22:37
and
22:38
add
22:38
value
22:38
from
22:38
a
22:38
business
22:38
and
22:39
strategy
22:39
perspective
22:40
up
22:40
front,
22:40
especially
22:40
when
22:40
it's
22:41
necessary
22:41
before
22:41
the
22:41
day
22:41
to
22:42
work.
22:42
But
22:43
in
22:44
any
22:44
case,
22:44
and
22:44
it's
22:44
funny
22:45
how
22:45
often
22:45
it
22:45
boils
22:45
down
22:46
to
22:46
what
22:46
is
22:46
your
22:47
shared
22:47
definition
22:47
of
22:47
success
22:48
for
22:48
this
22:48
business?
22:49
And
22:49
how
22:49
do
22:49
you
22:50
know
22:50
when
22:50
you,
22:50
when
22:51
you've
22:51
got
22:51
there?
22:51
Like,
22:51
how
22:52
are
22:52
you
22:52
going
22:52
to
22:52
know
22:53
when
22:53
you've
22:53
got
22:53
there?
22:54
And
22:54
sometimes
22:55
those
22:56
two
22:56
seemingly
22:56
innocuous
22:57
questions
22:57
can
22:57
be
22:59
really
22:59
powerful
22:59
ones
23:02
to
23:02
ask
23:02
and
23:02
pull
23:02
out.
23:03
You
23:03
can
23:03
help
23:03
the
23:03
business
23:03
get
23:04
clear
23:04
on
23:04
the
23:04
strategy.
23:04
You
23:05
also
23:05
help
23:05
the
23:06
data
23:06
team,
23:06
whether
23:06
they're
23:06
your
23:07
team
23:07
or
23:07
whether
23:07
the
23:07
client's
23:08
data
23:08
team
23:09
help
23:09
feel
23:11
get
23:11
more
23:11
of
23:12
a
23:12
straight
23:12
line
23:12
to
23:12
why
23:13
and
23:13
how
23:13
they're
23:13
supporting
23:14
the
23:14
business.
23:14
And
23:14
it
23:14
helps
23:15
them
23:16
then
23:17
often
23:18
unearth
23:18
the
23:18
insights
23:19
that
23:19
are
23:19
going
23:19
to
23:19
make
23:19
a
23:19
difference
23:20
that
23:20
they
23:20
wouldn't
23:20
have
23:20
thought
23:21
to.
23:22
Wouldn't
23:22
have
23:22
thought
23:23
to
23:23
position
23:23
otherwise.
23:24
Exactly.
23:24
Exactly.
23:26
That's
23:26
completely
23:27
it.
23:27
And
23:27
to
23:28
your
23:28
point,
23:28
the
23:28
first
23:29
question
23:29
is
23:29
always
23:30
what
23:30
tool
23:30
are
23:30
we
23:31
going
23:31
to
23:31
use?
23:31
But
23:31
it
23:32
should
23:32
be
23:32
like
23:32
the,
23:33
the
23:33
fourth
23:34
or
23:34
fifth
23:34
or
23:34
sixth
23:35
question
23:35
because
23:36
to
23:36
your
23:36
point,
23:36
as
23:36
long
23:37
as
23:37
you
23:37
know
23:37
those
23:37
things,
23:38
you
23:38
can
23:38
use
23:39
any
23:39
tool
23:39
you
23:39
want
23:40
to
23:40
get
23:40
there.
23:40
I
23:41
mean,
23:41
I
23:41
don't
23:41
see
23:42
like
23:42
there
23:42
are
23:42
differences
23:43
between
23:44
Tableau
23:44
and
23:44
Power
23:44
BI
23:45
or
23:46
gcp,
23:46
AWS
23:47
and
23:47
Azure.
23:47
But
23:47
like
23:49
they're
23:49
not
23:49
that
23:50
important.
23:51
They're
23:52
all
23:52
kind
23:52
of
23:52
similar
23:53
technologies.
23:53
Like
23:54
you're,
23:54
if
23:54
you
23:55
go
23:55
back
23:55
200
23:56
years
23:56
to
23:57
make
23:57
a
23:57
book,
23:59
a
23:59
printing
23:59
press
23:59
is
24:00
a
24:00
printing
24:00
press
24:00
and
24:01
you're
24:01
not
24:01
going
24:01
to
24:01
like
24:02
quibble
24:02
over
24:03
what
24:03
printing
24:03
press,
24:04
what
24:04
brand
24:04
of
24:04
printing
24:05
press
24:05
to
24:05
use,
24:05
you're
24:06
going
24:06
to
24:06
kind
24:06
of
24:06
quibble
24:06
over,
24:07
okay,
24:07
what's
24:07
the
24:07
content
24:07
of
24:08
the
24:08
book
24:08
of
24:08
whether
24:08
I
24:08
should
24:08
print
24:08
it
24:09
or
24:09
not?
24:09
And
24:09
that's
24:09
where
24:10
people
24:10
should
24:10
be
24:10
focusing
24:11
their,
24:11
their
24:11
attention
24:11
and
24:12
they
24:12
just
24:12
don't.
24:13
Yeah,
24:13
absolutely.
24:13
And
24:14
my
24:14
answer
24:14
is
24:14
almost
24:15
often
24:15
like
24:15
it,
24:17
the
24:17
choice
24:17
of
24:17
BI
24:17
tool
24:18
almost
24:18
depends
24:18
more
24:18
on
24:18
you
24:20
Mr.
24:20
Or
24:20
Mrs.
24:21
Client
24:21
than
24:21
it
24:21
does
24:21
on
24:21
me.
24:22
Because
24:22
it
24:23
depends,
24:23
you
24:23
know,
24:23
what
24:24
enterprise
24:25
tool
24:25
set
24:25
you've
24:25
got.
24:25
Like
24:26
are
24:26
you
24:26
a
24:26
full
24:26
on
24:26
Microsoft
24:27
shop?
24:28
Have
24:28
you
24:29
like
24:29
swallowed
24:30
all
24:30
the
24:30
Salesforce
24:30
Kool
24:31
Aid
24:31
and
24:32
you
24:32
know,
24:32
bought
24:32
all
24:33
of
24:33
their
24:33
extensions
24:33
and
24:34
you
24:34
know,
24:34
your
24:34
elbows
24:35
deep
24:35
into
24:36
Salesforce
24:36
and
24:37
using
24:37
it
24:37
as
24:37
your
24:37
enterprise
24:37
data
24:38
warehouse
24:38
as
24:38
well
24:38
as
24:38
your
24:39
CRM
24:39
as
24:39
well
24:39
as,
24:40
you
24:40
know,
24:40
having
24:40
it
24:40
make
24:40
coffee
24:41
for
24:41
you
24:41
and
24:41
say
24:41
good
24:42
morning
24:42
to
24:42
you
24:42
everyone
24:42
when
24:43
you
24:43
get
24:43
in
24:43
the
24:43
office
24:43
and
24:45
all
24:45
of
24:45
the
24:45
other
24:45
wonderful
24:46
things
24:46
that
24:46
Salesforce
24:47
does.
24:47
Like
24:47
if
24:47
that's
24:48
you,
24:48
then
24:48
tableau
24:48
is
24:48
a
24:48
great
24:49
choice,
24:49
right?
24:51
Or
24:51
if
24:51
you're
24:51
all
24:52
in
24:52
on
24:52
Copilot
24:52
and
24:53
all
24:53
your
24:54
backends
24:54
on
24:54
Azure
24:55
and
24:55
whatever
24:55
else,
24:55
then
24:56
sure,
24:56
like
24:56
Power
24:56
BI
24:57
is
24:57
probably
24:57
going
24:57
to
24:57
be
24:57
free,
24:58
right?
24:58
And
24:59
it
24:59
does
24:59
most
24:59
of
24:59
what
25:00
all
25:00
the
25:00
other
25:00
stuff
25:00
does.
25:01
So
25:03
yeah,
25:04
the
25:04
choices
25:04
BI
25:05
tools
25:05
I
25:06
often
25:06
refer
25:06
to
25:06
as.
25:07
It's
25:07
the
25:07
cherry
25:09
on
25:09
the
25:09
top
25:09
of
25:09
the
25:10
cake.
25:10
Like
25:10
after
25:10
we've
25:11
decided
25:11
what
25:11
sort
25:12
of
25:12
cake
25:12
we
25:12
want,
25:13
whipped
25:13
all
25:13
the
25:13
recipe
25:13
together,
25:14
baked
25:14
it
25:14
in
25:14
the
25:14
oven,
25:15
cut
25:15
it
25:15
in
25:15
half,
25:16
add
25:16
the
25:16
icing.
25:17
Okay,
25:17
now
25:17
let's
25:18
talk
25:18
about
25:18
BI
25:18
tools,
25:19
right?
25:19
Because
25:20
now
25:20
we've
25:20
got
25:20
information
25:20
that's
25:21
useful
25:21
to
25:21
you,
25:21
that's
25:21
well
25:22
controlled
25:22
and
25:22
well
25:22
governed
25:23
and
25:23
automated
25:24
as
25:24
much
25:24
as
25:24
is
25:24
sensible
25:25
and
25:25
then
25:25
we
25:25
can
25:25
get
25:26
somewhere.
25:29
I
25:29
talked
25:29
about
25:29
similarities
25:30
that
25:30
we
25:30
have
25:31
in
25:31
our
25:31
approach.
25:32
Like
25:32
what
25:33
threads
25:33
did
25:33
you
25:33
see
25:33
across
25:34
the
25:34
25
25:34
to
25:35
30
25:35
data
25:35
leaders
25:36
that
25:36
you
25:36
spoke
25:37
to?
25:37
What
25:37
are
25:37
kind
25:37
of
25:37
non
25:38
functional
25:38
or
25:39
softer
25:39
skills
25:40
do
25:40
those
25:40
folks
25:41
all
25:41
have
25:41
in
25:41
common?
25:42
CEOs?
25:42
If
25:43
you're
25:43
still
25:43
making
25:43
big
25:43
decisions
25:44
based
25:44
on
25:45
outdated
25:45
dashboard,
25:46
conflicting
25:46
numbers
25:47
and
25:47
manual
25:48
reports,
25:48
then
25:48
you're
25:48
not
25:48
leading
25:49
with
25:49
confidence.
25:49
You're
25:50
not
25:50
alone.
25:50
Most
25:50
5
25:51
million
25:51
plus
25:51
businesses
25:52
have
25:52
this
25:53
exact
25:53
struggle.
25:54
And
25:54
your
25:54
tech
25:54
stack
25:55
and
25:55
platforms
25:56
feel
25:56
like
25:56
they're
25:56
duct
25:57
taped
25:57
together
25:57
worse
25:58
every
25:58
week
25:58
that
25:59
goes
25:59
by.
25:59
You're
25:59
still
26:00
flying
26:00
blind.
26:01
And
26:01
if
26:01
AI
26:01
is
26:01
part
26:01
of
26:02
your
26:02
roadmap,
26:02
well
26:03
you
26:03
can
26:03
forget
26:03
about
26:04
it
26:04
because
26:04
clean
26:04
connected
26:05
data
26:05
is
26:06
step
26:06
one.
26:06
So
26:06
you're
26:07
still
26:07
in
26:07
the
26:07
starting
26:07
box
26:08
while
26:08
others
26:08
are
26:08
running
26:09
ahead
26:09
of
26:09
you.
26:09
That's
26:10
why
26:10
we
26:10
so
26:10
we
26:10
created
26:10
the
26:11
free
26:11
5
26:11
minute
26:12
data
26:12
maturity
26:12
assessment.
26:13
It's
26:13
fast,
26:14
it's
26:14
free
26:15
and
26:15
it
26:15
shows
26:15
you
26:15
where
26:15
your
26:16
business
26:16
stands
26:17
and
26:17
what's
26:17
holding
26:17
you
26:17
back.
26:18
You'll
26:18
walk
26:18
away
26:18
With
26:19
a
26:19
clear
26:19
score,
26:19
a
26:20
snapshot
26:20
of
26:20
your
26:20
current
26:21
systems
26:21
and
26:22
insight
26:22
into
26:22
what
26:22
it
26:23
will
26:23
take
26:23
to
26:24
build
26:24
a
26:24
data
26:24
infrastructure
26:25
to
26:25
support
26:25
your
26:25
ambition.
26:26
It's
26:26
the
26:26
same
26:26
approach
26:27
I've
26:27
used
26:27
inside
26:28
global
26:28
firms
26:28
like
26:28
Capital
26:29
One,
26:29
IBM
26:30
and
26:30
Accenture,
26:31
and
26:31
now
26:31
it's
26:31
adapted
26:32
for
26:32
fast
26:32
scaling
26:33
businesses
26:33
like
26:33
yours.
26:34
We've
26:34
helped
26:35
executive
26:35
teams
26:36
gain
26:36
clarity,
26:36
reduce
26:37
friction
26:37
and
26:38
make
26:38
better
26:38
decisions
26:39
with
26:39
the
26:39
data
26:39
they
26:40
already
26:40
have.
26:40
No
26:41
giant
26:41
software
26:41
overhaul,
26:42
no
26:42
disruption
26:42
to
26:43
your
26:43
team,
26:43
no
26:44
data
26:44
science
26:44
degree
26:45
required.
26:45
Also
26:46
no
26:47
magic
26:47
wand
26:47
apps
26:48
that
26:48
are
26:48
too
26:48
good
26:49
to
26:49
be
26:49
true
26:49
and
26:50
sell
26:50
a
26:50
dream
26:50
that
26:51
is
26:51
effectively
26:51
only
26:51
papering
26:52
over
26:52
the
26:52
cracks
26:53
of
26:53
structural
26:54
data
26:54
issues.
26:54
This
26:55
is
26:55
about
26:55
giving
26:55
CEOs
26:56
real
26:56
visibility
26:57
and
26:57
helping
26:58
you
26:58
lead
26:58
with
26:58
facts,
26:59
not
26:59
friction.
27:00
So
27:00
if
27:00
you're
27:00
ready
27:00
to
27:00
stop
27:01
getting
27:01
guessing
27:01
and
27:01
start
27:02
leading
27:02
with
27:02
real
27:02
data
27:03
clarity,
27:04
take
27:04
our
27:04
free
27:04
assessment.
27:05
It
27:05
only
27:05
takes
27:06
five
27:06
minutes.
27:06
You'll
27:07
get
27:07
immediate
27:07
insight
27:07
on
27:08
your
27:08
current
27:08
maturity
27:09
and
27:09
just
27:09
what's
27:09
possible
27:10
next.
27:10
Click
27:10
below
27:11
to
27:11
get
27:11
started.
27:12
You've
27:12
scaled
27:12
your
27:13
sales,
27:13
your
27:13
operations,
27:14
your
27:14
sales
27:15
team.
27:15
Now
27:16
it's
27:16
time
27:16
to
27:16
scale
27:16
your
27:17
data.
27:17
I've
27:17
led
27:17
data
27:18
transformations
27:18
for
27:19
some
27:19
of
27:19
the
27:19
world's
27:19
most
27:19
complex
27:20
companies
27:20
and
27:21
Now
27:21
I
27:21
help
27:22
CEOs
27:22
and
27:22
leadership
27:23
teams
27:23
just
27:23
like
27:24
yours
27:24
turn
27:24
data
27:25
into
27:25
a
27:25
real
27:25
advantage.
27:27
Let's
27:27
get
27:27
started.
27:27
I
27:28
think
27:28
all
27:28
of
27:28
them
27:28
said
27:29
when
27:29
I
27:29
asked
27:29
about
27:29
kind
27:30
of
27:30
success
27:30
is
27:31
is
27:32
really
27:32
thinking
27:33
from
27:33
the
27:33
business
27:33
outcomes
27:34
perspective.
27:35
I
27:35
think
27:35
that
27:36
was
27:36
the
27:36
real
27:37
through
27:37
line
27:38
of
27:38
of
27:38
how
27:39
they
27:39
succeeded
27:39
and
27:39
how
27:40
they
27:40
got
27:40
to
27:40
where
27:40
they
27:40
were.
27:41
A
27:41
lot
27:41
of
27:41
them
27:41
said
27:41
I
27:42
spent
27:42
too
27:42
much
27:42
time
27:42
on
27:42
technical
27:43
when
27:43
I
27:43
was
27:43
younger
27:44
and
27:45
it
27:45
wasn't
27:45
until
27:45
I
27:46
started
27:46
talking
27:46
to
27:46
people
27:46
and
27:47
becoming
27:47
best
27:47
friends
27:48
with
27:48
like
27:48
the
27:48
CFO
27:49
and
27:50
that
27:50
I
27:50
really
27:50
understood
27:51
what
27:51
what
27:51
I
27:52
needed
27:52
to
27:52
do.
27:54
And
27:54
then
27:55
the
27:55
other
27:55
thing
27:55
too
27:56
is
27:56
their
27:56
ability
27:57
to
27:57
kind
27:57
of
27:58
learn
27:58
to
27:58
lean
27:58
on
27:59
others.
28:00
I
28:00
think
28:00
data
28:01
when
28:01
you
28:02
start
28:02
out,
28:02
although
28:03
we've
28:03
got
28:03
a
28:03
great
28:03
community,
28:04
although
28:04
everyone
28:05
talks
28:05
about
28:05
being
28:05
a
28:05
team
28:06
sport,
28:06
it's
28:07
really
28:07
an
28:07
individual
28:08
kind
28:08
of
28:09
contributor
28:09
role
28:09
for
28:10
the
28:10
most
28:10
part.
28:11
And
28:11
people
28:11
really
28:12
have
28:12
to
28:12
kind
28:12
of
28:13
either
28:13
learn
28:13
to
28:14
become
28:14
less
28:14
of
28:14
an
28:14
individual
28:15
contributor
28:15
and
28:15
manage
28:16
people
28:17
or
28:17
even
28:18
or
28:18
share
28:18
their
28:19
best
28:19
practice
28:19
or
28:20
do
28:20
better
28:21
in
28:21
documentation
28:23
to
28:23
succeed.
28:24
You're
28:24
not
28:24
going
28:24
to
28:25
succeed
28:25
as
28:25
an
28:25
individual
28:26
because
28:26
there's
28:27
too
28:27
much
28:27
to
28:27
do
28:27
and
28:27
there's
28:28
too
28:28
much
28:28
to
28:28
know.
28:30
You
28:30
really
28:30
have
28:31
to
28:31
lean
28:31
on
28:31
other
28:31
skill
28:32
sets.
28:32
Like
28:33
for
28:33
example
28:33
in
28:33
my
28:33
company
28:35
I'm
28:35
the
28:35
head
28:35
of
28:35
data
28:36
strategy
28:36
and
28:36
I
28:36
also
28:37
help
28:37
run
28:38
the
28:38
kind
28:38
of
28:38
analytics
28:39
and
28:39
data
28:39
science
28:40
projects
28:40
when
28:41
they
28:41
come
28:41
about.
28:41
And
28:42
I
28:42
also
28:42
I
28:42
do
28:42
lean
28:43
in
28:43
on
28:44
engineering
28:44
and
28:45
architecture
28:45
too
28:46
because
28:46
they
28:46
have
28:46
strategic
28:46
lenses
28:47
on
28:47
it.
28:47
But
28:48
like
28:48
if
28:48
I'm
28:49
going
28:49
to
28:49
a
28:49
client
28:49
and
28:49
I'm
28:50
talking
28:50
about
28:50
a
28:50
customer
28:50
data
28:51
model,
28:51
which
28:51
I
28:51
am
28:52
right
28:52
now,
28:53
I'm
28:53
going
28:53
to
28:54
lean
28:54
on
28:55
our
28:55
principal
28:56
engineer
28:56
who
28:57
has
28:57
proper
28:58
software
28:59
engineering
29:00
principle
29:02
engineering
29:02
principles
29:03
in
29:03
his
29:03
background.
29:03
And
29:03
he's
29:04
done
29:04
it
29:04
all
29:05
right.
29:05
And
29:06
I
29:06
learned
29:06
from
29:06
him
29:07
because
29:07
we
29:08
kind
29:08
of
29:08
complement
29:08
one
29:09
another.
29:09
So
29:10
it
29:10
really
29:10
is
29:11
a
29:11
team
29:11
sport
29:12
and
29:12
I
29:12
think
29:12
data
29:13
leaders
29:13
who
29:13
succeed
29:14
get
29:14
that.
29:16
And
29:16
you
29:17
really
29:17
need
29:17
to
29:17
kind
29:18
of
29:18
leverage
29:18
some
29:18
of
29:18
these
29:18
things
29:18
to
29:19
grow
29:19
in
29:19
your
29:19
career
29:19
as
29:19
a
29:20
data
29:20
person.
29:21
Otherwise
29:21
you're
29:22
just
29:22
gonna
29:22
be
29:22
stuck
29:22
being
29:22
an
29:23
individual
29:23
contributor
29:24
and
29:25
you'll
29:25
be
29:25
expendable
29:26
at
29:26
some
29:26
point.
29:27
I
29:27
blame
29:27
the
29:28
software
29:28
engineers.
29:29
The
29:30
period
29:30
we
29:30
went
29:30
through
29:32
in
29:32
the,
29:34
Maybe
29:34
I
29:34
think
29:34
2018
29:35
through
29:35
2021,
29:36
when
29:37
the
29:37
unicorn
29:38
full
29:38
stack
29:39
software
29:39
engineer
29:39
was
29:40
the
29:40
most
29:40
sought
29:40
after
29:41
an
29:41
on
29:41
the
29:41
planet
29:42
and
29:43
they
29:43
were
29:43
writing
29:43
their
29:43
own
29:44
paychecks
29:44
and
29:46
wherever
29:46
they
29:46
wanted
29:47
to
29:47
go.
29:47
I
29:48
wonder
29:48
how
29:48
much
29:48
of
29:48
a
29:48
myth
29:48
that
29:49
actually
29:49
was
29:49
as
29:49
well.
29:50
Is
29:50
anyone
29:51
really,
29:51
can
29:52
anyone
29:52
really
29:52
have
29:53
both
29:53
the
29:53
breadth
29:54
and
29:54
the
29:54
depth
29:55
of
29:55
front
29:55
end,
29:56
back
29:56
end
29:56
integration
29:57
data?
29:57
All
29:58
the
29:58
things
29:58
that
29:58
you
29:58
need
29:58
to
29:58
be
29:58
to
29:59
be
29:59
that
29:59
unicorn?
30:00
Maybe
30:00
the
30:00
occasional
30:01
exceptional
30:01
few
30:02
do
30:03
and
30:04
maybe
30:04
that
30:04
kind
30:04
of
30:04
bled
30:04
across
30:05
to
30:05
the
30:05
world
30:05
of
30:05
data
30:05
and
30:06
lured
30:07
people
30:07
down
30:07
a
30:07
path
30:08
that
30:08
probably
30:08
wasn't
30:09
the
30:09
best
30:09
one.
30:09
Yeah,
30:09
I
30:10
mean
30:10
I
30:10
can
30:10
see
30:10
people
30:12
being
30:12
a
30:12
unicorn,
30:13
but
30:14
I
30:14
think
30:14
that
30:14
existed
30:15
a
30:15
lot
30:16
more
30:16
five
30:16
years
30:17
ago
30:17
when
30:17
the
30:18
data
30:18
ecosystem
30:19
wasn't
30:19
as
30:20
complex
30:20
as
30:20
it
30:20
is
30:20
now.
30:21
Now
30:22
to
30:22
run
30:23
something
30:23
and
30:23
production
30:23
as
30:24
something,
30:24
you
30:24
need
30:24
to
30:24
have
30:25
really
30:25
good
30:26
experience,
30:26
not
30:26
to
30:28
run
30:29
your
30:29
bill
30:29
up
30:29
super
30:30
high.
30:31
You
30:32
want
30:32
to
30:32
actually
30:33
build
30:33
this
30:33
in
30:34
a
30:34
way
30:34
that's
30:34
scalable
30:35
and
30:36
well
30:37
built
30:37
and
30:37
efficient.
30:39
You
30:39
need
30:39
to
30:39
lean
30:40
into
30:40
certain
30:41
areas
30:41
of
30:41
experience.
30:42
Just
30:43
so
30:43
many
30:43
organizations
30:44
don't
30:44
do
30:44
this.
30:45
And
30:46
like
30:46
maybe
30:47
I'm
30:47
speaking
30:47
from
30:47
being
30:47
a
30:47
consultant
30:48
and
30:48
I
30:48
want
30:48
you
30:48
all
30:49
to
30:49
buy
30:49
me
30:50
and
30:50
my
30:50
services
30:51
as
30:51
a
30:51
consultant.
30:51
But
30:53
in
30:53
the
30:53
truth
30:53
of
30:53
the
30:53
matter
30:54
is
30:55
they're
30:55
throwing
30:55
away
30:56
money
30:56
because
30:58
they're
30:58
hiring
30:59
more
30:59
and
30:59
more
30:59
resources
31:00
to
31:00
manage
31:01
poorly
31:02
built
31:03
data
31:03
models
31:03
and
31:03
data
31:04
infrastructure
31:04
and
31:04
data
31:05
pipelines.
31:06
Meanwhile,
31:07
they're
31:07
paying
31:07
snowflake
31:08
or
31:08
databricks
31:09
a
31:09
ton
31:09
of
31:09
money
31:09
because
31:10
those
31:11
are
31:12
built
31:12
inefficiently.
31:13
And
31:14
then
31:14
they're
31:14
saying
31:14
no,
31:15
we
31:15
don't
31:15
have
31:15
enough
31:15
money
31:16
to
31:16
like
31:17
rebuild
31:17
this
31:17
strategically
31:18
and
31:19
like,
31:19
well,
31:19
your
31:20
long
31:20
term
31:20
gain
31:21
in
31:22
savings
31:23
will
31:23
actually
31:23
probably
31:24
outstrip
31:25
what
31:25
you're
31:25
going
31:25
to
31:25
pay
31:25
up
31:25
front
31:26
to
31:26
do
31:26
this
31:26
properly.
31:28
But
31:28
organizations
31:29
don't
31:30
get
31:30
that.
31:30
They're
31:30
quite
31:31
reactive
31:31
in
31:31
this
31:32
nature
31:32
and
31:32
you
31:32
really
31:33
have
31:33
to
31:33
push
31:33
them
31:34
to
31:34
do
31:34
that.
31:34
And,
31:35
and
31:36
I
31:36
think
31:36
that
31:36
expertise
31:38
needs
31:39
to
31:39
be
31:40
put
31:40
more
31:40
on
31:41
a
31:41
pedestal
31:42
in
31:42
the
31:43
data
31:43
world
31:43
because
31:44
we
31:44
get
31:46
so
31:46
bogged
31:46
down
31:47
with
31:48
really
31:48
poorly
31:49
built
31:49
pipelines,
31:50
really
31:50
poorly
31:51
built
31:51
code
31:52
and,
31:53
and
31:54
it
31:54
ruins
31:55
efficiency,
31:56
it
31:56
ruins
31:56
the
31:56
value
31:56
of
31:57
data
31:57
across
31:57
organizations.
31:58
And
31:59
we,
32:00
we
32:00
don't,
32:00
we
32:00
as
32:00
an
32:00
industry
32:01
have
32:02
never
32:02
put
32:02
a
32:02
stop
32:02
to
32:03
it.
32:03
Yeah.
32:03
And
32:04
what's
32:04
actually,
32:04
what's
32:05
unhelpful
32:05
to
32:05
people
32:05
like
32:05
you
32:06
and
32:06
I
32:06
is
32:06
that
32:07
there
32:07
are
32:07
shops
32:07
out
32:07
there
32:08
who
32:08
will
32:08
come
32:08
in
32:09
and
32:09
slap
32:10
a
32:10
nice
32:10
looking
32:10
automation
32:11
layer
32:11
or
32:11
a
32:11
nice
32:11
looking
32:12
dashboard
32:12
layer
32:12
on
32:13
top
32:13
of
32:13
like
32:13
fundamentally
32:14
broken
32:14
data
32:14
infrastructure,
32:15
charge
32:16
a
32:16
bunch
32:16
of
32:16
money
32:16
for
32:17
it
32:17
and
32:17
then
32:18
kind
32:18
of
32:18
walk
32:18
away
32:19
and
32:20
pop
32:20
the
32:21
champagnes
32:21
and
32:21
go
32:21
on
32:22
to
32:22
the
32:22
next
32:22
100%.
32:24
And
32:24
I've
32:25
been
32:25
through
32:25
the
32:25
hard
32:25
sell
32:25
that
32:26
you've
32:26
been
32:26
through.
32:26
Like
32:26
I
32:27
go
32:27
to
32:27
all
32:27
the
32:27
effort
32:27
of
32:28
making
32:28
sure
32:28
I
32:28
put
32:28
in
32:29
into
32:29
detailed
32:29
project
32:30
plans
32:30
so
32:30
that
32:30
clients
32:31
can
32:31
see,
32:31
including
32:32
non
32:32
technical
32:32
clients.
32:33
Like
32:33
this
32:33
is
32:34
how
32:34
much
32:34
we
32:34
have
32:34
to
32:34
invest
32:35
in
32:36
EC2
32:36
efficiency.
32:37
Like
32:37
this
32:37
is
32:38
where,
32:38
this
32:38
is
32:38
where
32:39
we're
32:39
doing
32:39
rehydration.
32:40
This
32:40
is
32:40
how
32:41
we're
32:41
allocating
32:41
resources.
32:42
This
32:42
one,
32:42
we're
32:42
shutting
32:43
machines
32:43
off
32:43
and
32:43
turning
32:43
them
32:43
back
32:44
on
32:44
again
32:44
in
32:44
an
32:44
automated
32:45
way
32:45
to
32:45
save
32:45
what
32:46
might
32:46
seem
32:46
like
32:46
a
32:46
small
32:46
amount
32:47
of
32:47
money
32:48
but
32:48
like
32:48
over
32:48
365
32:49
days
32:50
is
32:50
actually
32:50
quite
32:50
a
32:50
lot,
32:51
a
32:51
lot
32:51
of
32:51
money
32:52
that
32:52
you
32:52
can
32:53
invest
32:53
somewhere
32:54
else.
32:54
So
32:54
that
32:55
efficiency.
32:55
And
32:55
the
32:56
second
32:56
one
32:56
is
32:56
the
32:56
automated
32:57
DQ
32:57
checks.
32:57
Data
32:58
quality
32:58
checks.
32:59
Sorry
32:59
for
32:59
those,
33:00
I
33:00
always
33:01
slip
33:01
into
33:01
acronyms.
33:02
The
33:02
automated
33:02
data
33:02
quality
33:03
checking
33:04
takes
33:05
quite
33:05
a
33:05
lot
33:05
of
33:05
investment
33:05
because
33:06
not
33:06
only
33:06
do
33:06
you
33:06
have
33:06
to
33:07
learn
33:07
a
33:07
client's
33:07
business,
33:07
but
33:08
you
33:08
have
33:08
to
33:08
learn
33:08
the
33:09
specific
33:09
nuances,
33:10
sometimes
33:10
a
33:10
field
33:11
and
33:11
column
33:11
level
33:11
of
33:12
like
33:12
where
33:12
might
33:13
this
33:13
go
33:13
off?
33:14
Or
33:14
what
33:14
would
33:15
a
33:15
fail
33:15
scenario
33:16
look
33:16
like
33:16
for
33:16
this
33:17
data
33:19
and
33:19
then
33:19
run
33:19
it
33:19
and
33:20
fix
33:20
it.
33:20
And
33:20
you
33:21
and
33:21
I
33:21
both
33:21
know
33:21
that's
33:21
not
33:22
like,
33:22
oh,
33:23
let's
33:23
press
33:24
a
33:24
switch
33:24
and
33:24
turn
33:24
data
33:25
quality
33:25
on.
33:26
The
33:26
understanding
33:27
you
33:27
need
33:27
is
33:27
deeper.
33:28
And
33:28
then
33:28
as
33:28
you
33:29
say
33:29
the
33:29
engineering
33:29
skills
33:29
you
33:30
need
33:30
to
33:30
actually
33:30
implement
33:31
that
33:31
in
33:32
a
33:32
way
33:32
which
33:32
is
33:32
going
33:32
to
33:32
stand
33:33
the
33:33
test
33:33
of
33:33
time
33:33
for
33:33
whether
33:34
businesses
33:34
know
33:34
and
33:35
whether
33:35
businesses
33:35
going.
33:36
Yeah.
33:36
So
33:36
I
33:36
will,
33:37
I
33:37
will
33:37
swear
33:38
the
33:38
oath
33:38
with
33:38
you
33:38
today,
33:39
Dylan,
33:39
to
33:41
represent
33:41
that
33:41
stuff
33:43
and
33:43
shout
33:44
louder
33:44
about
33:44
it.
33:45
Maybe
33:45
I'll
33:45
draw
33:45
an
33:45
Excalidraw.
33:46
Who
33:46
knows.
33:47
Well,
33:47
yeah,
33:48
and
33:48
to
33:48
build
33:48
on
33:49
that
33:49
and
33:50
be
33:50
quick
33:50
on
33:50
it.
33:51
But
33:51
like
33:52
I
33:52
think
33:53
there's,
33:53
there's
33:54
two
33:54
big
33:55
issues
33:55
to
33:55
it.
33:55
One,
33:56
I
33:56
think
33:56
it
33:56
touched
33:56
to
33:57
what
33:57
you
33:57
were
33:57
saying
33:57
initially
33:58
of
33:58
like
33:58
just
33:59
poor
33:59
delivery
34:00
and
34:00
like
34:01
I
34:02
recently
34:02
with
34:02
a
34:02
client,
34:03
we,
34:03
we
34:04
were
34:04
building
34:04
them
34:04
a
34:04
kind
34:04
of
34:05
single
34:05
customer
34:05
view.
34:06
And
34:06
we
34:06
built
34:06
them
34:06
the
34:06
first
34:07
phase
34:07
and
34:07
I
34:08
said,
34:08
like,
34:08
we're
34:09
not
34:09
going
34:09
to
34:09
continue
34:09
because
34:10
we
34:10
need
34:10
to
34:10
build
34:10
a
34:10
customer
34:11
data
34:11
model
34:11
first.
34:11
Because
34:12
none
34:12
of
34:12
your
34:12
sources
34:12
talk
34:13
to
34:13
each
34:13
other.
34:13
Yep.
34:14
And
34:14
so
34:14
we
34:15
kind
34:15
of
34:15
put
34:15
a
34:15
pause
34:15
on
34:16
that
34:16
and
34:16
like
34:17
cut
34:17
revenue
34:18
out
34:18
of
34:18
what
34:19
I
34:19
could
34:19
sell
34:20
to
34:20
then
34:21
say.
34:21
And
34:21
now
34:21
we're
34:21
kind
34:22
of
34:22
spinning
34:22
up.
34:22
I
34:22
mean,
34:22
I'm
34:23
part
34:23
of
34:23
the
34:23
other,
34:23
the
34:23
customer
34:24
data
34:24
model
34:24
as
34:24
well.
34:24
But
34:24
like,
34:25
we
34:25
need
34:26
to
34:26
make
34:26
sure
34:26
that
34:26
we're
34:26
doing
34:27
this
34:27
right
34:27
if
34:27
we're
34:27
going
34:27
to
34:27
do
34:28
it
34:28
at
34:28
all.
34:28
And
34:28
I
34:28
don't
34:29
think
34:29
enough
34:30
consultancies,
34:30
I
34:31
don't
34:31
think
34:31
enough
34:31
people
34:32
have
34:32
the
34:33
cojones
34:34
to
34:34
actually
34:35
say
34:35
that
34:35
and
34:36
follow
34:36
through
34:36
with
34:37
it.
34:37
I
34:37
think
34:37
a
34:37
lot
34:37
of,
34:38
and
34:38
a
34:38
lot
34:38
of,
34:38
I
34:38
mean,
34:38
this
34:39
is
34:39
why
34:39
I
34:39
don't
34:39
work
34:39
for
34:39
a
34:40
large
34:40
consultancy,
34:40
but
34:40
a
34:41
lot
34:41
of
34:41
large
34:41
consultancies
34:42
ship
34:42
it
34:42
out
34:42
to
34:43
offshore
34:44
or
34:44
nearshore
34:45
and
34:45
say,
34:45
let's
34:46
just
34:46
build
34:46
this
34:46
stuff.
34:46
And
34:47
then
34:47
it
34:47
completely
34:48
doesn't
34:48
work.
34:48
And
34:48
then
34:48
companies
34:49
have
34:49
to
34:49
redo
34:49
it
34:49
all
34:49
over
34:49
again.
34:50
So
34:50
I
34:50
have
34:50
a
34:50
really
34:51
big
34:51
problem
34:51
with
34:51
that
34:51
because
34:51
I
34:52
see
34:52
it
34:52
all
34:52
over
34:52
the
34:53
second
34:53
thing,
34:53
I
34:53
think
34:53
to
34:54
what
34:54
you're
34:54
saying,
34:55
the
34:55
data
34:56
quality
34:56
stuff.
34:56
And,
34:57
and
34:57
we,
34:57
we
34:58
do
34:58
rely
34:58
too
34:58
much
34:58
on
34:59
tools
34:59
and
34:59
technologies
35:00
to
35:00
do
35:00
all
35:00
these
35:00
things.
35:01
And
35:01
when
35:01
we
35:02
also
35:03
from
35:03
a
35:03
data
35:03
perspective,
35:04
when
35:04
we
35:04
do
35:04
a
35:05
technical
35:05
implementation,
35:06
when
35:06
we
35:07
think
35:07
about
35:07
new
35:07
technologies
35:08
to
35:08
do
35:08
these
35:08
types
35:09
of
35:09
things,
35:10
we
35:10
never
35:10
think
35:10
about
35:11
it
35:11
strategically.
35:12
I
35:12
have
35:12
not
35:13
once
35:14
seen
35:14
a
35:14
company
35:14
with
35:15
a
35:15
technology
35:15
strategy,
35:16
which
35:17
is
35:18
terrifying.
35:19
It's
35:19
actually
35:19
my
35:20
most
35:21
engaged
35:21
and
35:22
most
35:22
popular
35:24
article
35:24
in
35:24
the
35:24
in
35:25
the
35:25
Data
35:25
Ecosystem
35:26
newsletter.
35:26
People
35:27
loved
35:27
it
35:27
because
35:27
they're
35:28
like,
35:28
oh
35:28
my
35:28
gosh,
35:28
let's
35:29
think
35:29
about
35:29
technology
35:30
strategically.
35:30
That's
35:31
smart.
35:31
I'm
35:31
like,
35:31
yeah,
35:31
it's
35:32
what
35:32
you
35:32
should
35:32
probably
35:32
do
35:32
be
35:33
doing
35:33
at
35:33
the
35:33
same
35:33
time
35:33
if
35:33
you're
35:34
going
35:34
to
35:34
invest
35:34
like
35:35
millions
35:35
of
35:35
dollars
35:36
into
35:36
this.
35:37
But
35:38
to
35:38
think
35:38
about
35:39
technology
35:39
strategically,
35:40
you're
35:41
able
35:41
to
35:41
plan,
35:41
okay,
35:42
what
35:42
are
35:42
we
35:42
doing
35:43
in
35:43
the
35:43
future?
35:43
What
35:43
use
35:43
cases
35:44
do
35:44
we
35:44
actually
35:44
need
35:44
to
35:45
deliver
35:45
on
35:45
this?
35:45
And
35:46
how
35:46
is
35:46
technology
35:47
support
35:47
that?
35:48
And
35:49
if
35:49
we're
35:49
thinking
35:49
about,
35:50
for
35:50
example,
35:50
dq,
35:51
let's
35:52
set
35:52
our
35:52
standards
35:54
for
35:54
these
35:54
different
35:55
and
35:55
definitions
35:56
for
35:56
these
35:56
different
35:57
quality
35:57
metrics
35:58
and
35:58
different
35:59
parts
35:59
of
35:59
our
36:00
business
36:00
and
36:00
KPIs
36:01
before
36:02
we
36:02
invest
36:03
in
36:03
this
36:03
observability
36:04
tool.
36:05
But
36:06
companies
36:06
don't
36:06
do
36:07
that.
36:07
And
36:09
it
36:09
annoys
36:10
the
36:10
hell
36:10
out
36:11
of
36:11
me.
36:13
I'm
36:13
still
36:13
pretty
36:13
young,
36:14
but
36:14
as
36:14
soon
36:15
I'm
36:15
getting
36:15
older,
36:16
by
36:16
the
36:16
way,
36:17
by
36:17
the
36:17
amount
36:17
I
36:18
deal
36:18
with
36:18
this
36:18
stuff
36:19
and
36:19
just
36:19
kind
36:20
of
36:20
bang
36:20
my
36:20
head
36:20
against
36:20
the
36:21
wall
36:21
when
36:21
I
36:21
see
36:22
this
36:22
stuff
36:22
happen.
36:23
Yeah.
36:24
I
36:24
used
36:24
to
36:25
think
36:25
that
36:25
older
36:25
people
36:25
were
36:26
cynical
36:26
until
36:26
I
36:26
became
36:27
one
36:27
and
36:27
realized
36:27
it's
36:28
the
36:28
badge
36:28
that
36:28
you
36:28
earn
36:28
through
36:29
experience.
36:32
Oh,
36:32
this
36:32
again.
36:32
Good.
36:34
They're
36:35
good.
36:37
Hopefully
36:37
in
36:38
London
36:38
they've
36:38
taught
36:38
you
36:38
the
36:39
stiff
36:39
upper
36:39
lip
36:41
mentality.
36:42
Keep
36:42
calm
36:42
and
36:42
carry
36:43
on.
36:43
Right,
36:44
Keep
36:44
coming,
36:45
keep
36:45
plugging
36:45
on.
36:46
The
36:46
example
36:48
that
36:48
I've
36:48
seen
36:48
a
36:48
number
36:49
of
36:49
times
36:49
and
36:50
see
36:50
out
36:50
there
36:50
is
36:50
CRM
36:51
implementations
36:52
or
36:52
folks
36:53
will
36:53
come
36:53
and
36:53
say,
36:53
oh,
36:53
what
36:54
we
36:54
need
36:54
is
36:54
a
36:54
CRM.
36:55
Because
36:55
as
36:55
you
36:56
say,
36:56
what
36:57
they
36:57
actually
36:57
want
36:57
is
36:57
that
36:57
single
36:58
customer
36:58
view
36:58
that
36:58
you
36:58
were
36:58
talking
36:59
about
36:59
building
36:59
for
36:59
that
36:59
client.
37:00
They
37:00
actually
37:00
want
37:00
a
37:00
single
37:01
customer
37:01
view
37:01
so
37:01
they
37:01
can
37:01
see
37:02
the
37:02
touch
37:02
points.
37:02
And
37:03
in
37:04
some
37:04
cases,
37:04
and
37:05
I've
37:05
actually
37:05
said
37:05
this,
37:06
I
37:06
could
37:06
implement
37:07
a
37:07
CRM,
37:08
but
37:08
you
37:08
have
37:08
no
37:09
way
37:09
to
37:09
connect
37:10
what
37:10
your
37:10
customers
37:11
are
37:11
doing
37:11
here
37:11
with
37:11
what
37:11
they're
37:12
doing
37:12
here
37:12
with
37:12
what
37:12
they're
37:12
doing
37:13
here.
37:13
So
37:13
like
37:13
it's
37:14
really
37:14
of
37:14
no
37:14
value
37:14
to
37:15
you
37:15
until
37:15
you
37:15
fix
37:15
this
37:16
problem.
37:16
Like
37:17
you
37:17
can
37:17
put
37:17
all
37:18
the
37:18
data
37:18
in
37:18
one
37:18
place
37:18
all
37:18
you
37:19
like,
37:19
but
37:19
if
37:19
you
37:19
haven't
37:19
got
37:19
any
37:20
sort
37:20
of
37:20
key
37:20
to
37:20
join
37:21
it,
37:21
then
37:22
you
37:22
know
37:23
there's
37:23
going
37:23
to
37:23
be
37:23
no
37:23
value
37:24
on
37:24
there.
37:25
And
37:25
yet
37:26
there
37:26
are
37:26
countless
37:27
companies
37:27
out
37:27
there
37:27
that
37:27
would
37:28
merrily
37:29
charge
37:30
whatever
37:30
they
37:30
charge
37:31
to,
37:31
you
37:31
know,
37:32
go
37:32
and
37:32
recommend
37:33
HubSpot
37:33
and
37:34
roll
37:34
it
37:34
out
37:34
and
37:35
all
37:35
that
37:35
stuff,
37:35
modules
37:36
and
37:36
monthly
37:37
costs
37:37
and
37:37
whatever
37:37
else
37:39
without
37:39
delivering
37:39
that
37:40
business
37:40
value.
37:40
So
37:40
I,
37:41
yeah,
37:41
I'm
37:42
definitely
37:42
seeing
37:42
that
37:43
walking
37:43
that
37:43
bridge
37:44
is
37:44
the
37:44
critical
37:44
place
37:44
to
37:45
be.
37:45
Yeah,
37:46
yeah,
37:46
no,
37:46
I
37:46
see
37:47
that
37:47
too.
37:47
And
37:48
yeah,
37:49
and
37:50
the
37:50
other
37:50
issue
37:50
with
37:51
that
37:51
too
37:51
is,
37:52
is
37:52
those
37:52
CRM
37:53
tools
37:53
or
37:54
the
37:54
ERPs
37:54
or
37:55
whatever
37:55
they
37:55
are,
37:56
they're
37:57
essential
37:57
for
37:58
the
37:58
lifeblood
37:58
of
37:59
the
37:59
organization
37:59
to
38:00
the
38:00
day
38:00
to
38:00
day
38:00
on
38:01
some
38:01
of
38:01
these
38:01
things.
38:02
But
38:02
they
38:02
don't
38:03
sit
38:03
in
38:03
the
38:03
data
38:04
team.
38:04
No
38:04
one
38:05
asks
38:05
the
38:06
data
38:06
team
38:07
how
38:08
they
38:08
should
38:08
set
38:08
it
38:08
up,
38:09
how
38:09
they
38:09
should
38:09
use
38:10
it,
38:10
how
38:11
it
38:11
should
38:11
kind
38:12
of
38:12
talk
38:13
with
38:13
other
38:14
tools
38:14
and
38:14
systems
38:15
and
38:15
stuff
38:15
like
38:15
that.
38:16
But
38:16
at
38:16
a
38:17
certain
38:17
point
38:17
they
38:18
do
38:18
get
38:18
annoyed,
38:19
those
38:19
teams,
38:19
because
38:20
wait,
38:21
this
38:21
CRM
38:22
tool
38:22
doesn't
38:23
do
38:23
what
38:23
Salesforce
38:24
told
38:24
me
38:24
it
38:24
was
38:25
going
38:25
to
38:25
do.
38:25
Yes.
38:26
Yeah,
38:26
I
38:27
was
38:27
told
38:27
a
38:27
dream.
38:28
Yeah,
38:28
I
38:28
was,
38:29
I
38:29
thought
38:29
everything
38:30
was
38:30
connected
38:30
and
38:30
would
38:31
go
38:31
work
38:31
seamlessly
38:32
with
38:32
one
38:32
another.
38:32
It's
38:32
like,
38:33
no,
38:33
you
38:33
have
38:33
to
38:33
set
38:33
up
38:33
those
38:33
APIs
38:34
and
38:34
connect
38:34
it
38:35
to
38:35
your
38:35
Power
38:35
BI
38:36
dashboards
38:36
or
38:36
your
38:36
whatever.
38:38
And,
38:38
but
38:38
then,
38:39
I
38:39
mean,
38:39
and
38:39
I'm
38:40
not
38:40
digging
38:40
on
38:40
Salesforce
38:41
right
38:41
now,
38:41
but
38:42
then
38:42
Salesforce
38:43
account
38:43
managers
38:44
will
38:44
be
38:44
coming.
38:44
Well,
38:45
actually
38:45
you
38:45
can
38:45
do
38:45
that
38:45
if
38:46
you
38:46
buy
38:46
an
38:46
upgrade
38:47
to
38:47
data
38:47
clouds
38:50
and
38:50
they're
38:51
really
38:51
good.
38:51
Salesforce
38:52
is
38:52
in
38:52
every
38:52
company
38:53
I
38:53
work
38:53
with,
38:54
to
38:54
be
38:54
honest,
38:54
and
38:54
it's
38:54
a
38:55
great
38:55
piece
38:55
of
38:55
technology.
38:56
But
38:57
companies
38:58
are
38:58
buying
38:59
these
38:59
things
38:59
and
38:59
think
39:00
it
39:00
does
39:00
all
39:01
without
39:01
thinking,
39:01
oh,
39:02
you
39:02
actually
39:02
have
39:02
to
39:02
think
39:02
about
39:03
this
39:03
strategically,
39:03
about
39:03
why
39:04
I'm
39:04
using
39:04
this
39:04
and
39:05
how
39:05
to
39:05
use
39:05
it
39:05
better.
39:05
And
39:05
I
39:06
think
39:06
Salesforce
39:07
account
39:07
reps
39:08
also
39:08
want
39:08
you
39:08
to
39:08
think
39:08
about
39:08
that
39:09
stuff
39:09
too.
39:09
And
39:09
so
39:09
do
39:10
other
39:10
SaaS,
39:10
companies
39:11
and
39:11
vendors,
39:12
because
39:12
that
39:12
makes
39:13
you
39:13
use
39:13
it
39:13
more.
39:14
And
39:14
I've
39:14
heard
39:14
it
39:14
said
39:15
of
39:15
like,
39:15
when
39:15
we
39:16
get
39:16
this
39:16
new
39:16
CRM,
39:16
then
39:17
you
39:17
know,
39:17
the
39:17
quality
39:18
of
39:18
data
39:18
the
39:18
sales
39:18
team
39:18
are
39:18
putting
39:19
in
39:19
will,
39:19
will
39:19
improve.
39:20
But
39:20
yeah,
39:20
absolutely
39:21
not.
39:21
Like,
39:21
that's
39:22
the,
39:23
that's
39:23
another
39:23
CRM
39:24
thing
39:24
I've
39:24
walked
39:24
away
39:24
from.
39:25
Like,
39:25
until
39:25
your
39:26
sales
39:26
team
39:26
starts
39:26
putting
39:27
good
39:27
data
39:27
into
39:27
the
39:27
front
39:28
of
39:28
this,
39:28
like,
39:29
nothing
39:29
good
39:29
is
39:29
going
39:30
to
39:30
happen.
39:30
CRM
39:31
doesn't
39:31
represent,
39:31
it
39:32
doesn't
39:32
replace
39:33
free
39:33
text
39:33
input.
39:35
It's.
39:35
Oh,
39:36
yeah,
39:36
yeah,
39:36
just
39:36
type
39:37
what
39:37
you
39:37
want.
39:38
I,
39:39
Interestingly,
39:39
I
39:39
was
39:39
at
39:40
the,
39:40
I,
39:41
I,
39:41
I
39:41
mentioned
39:42
this
39:42
on,
39:42
on
39:42
LinkedIn
39:43
a
39:43
couple
39:43
of
39:43
weeks
39:43
back,
39:43
but
39:43
I
39:44
was
39:44
at
39:44
the
39:45
Alex
39:45
Hormozi's
39:45
scaling
39:46
workshop
39:46
and
39:46
he
39:46
actually
39:46
went
39:47
off
39:47
on
39:47
one
39:47
about
39:47
CRMs.
39:48
It
39:48
was
39:48
interesting
39:49
and
39:49
it
39:49
was
39:49
his
39:49
perspective
39:50
that
39:50
for
39:50
growing
39:50
companies,
39:51
you
39:52
know,
39:52
the
39:52
founder
39:52
should
39:52
always
39:53
be
39:53
heavily
39:53
involved
39:53
in
39:54
at
39:54
least
39:55
some
39:55
sort
39:55
of
39:55
leadership
39:56
role
39:56
of
39:56
any
39:56
CRM
39:57
implementation.
39:57
He's
39:58
talking
39:58
about
39:58
companies
39:59
in
39:59
kind
39:59
of
39:59
growth
39:59
stage
40:00
that
40:00
reach
40:01
a
40:01
point
40:01
where
40:01
it's
40:01
time
40:02
to
40:03
start
40:03
with
40:03
a
40:03
CRM.
40:04
But
40:04
he
40:05
said
40:05
he'd
40:05
made
40:05
the
40:05
mistake
40:06
himself
40:06
before
40:06
of
40:06
like,
40:07
if
40:07
you
40:07
hand
40:07
it
40:08
off
40:08
to
40:09
just
40:09
tech,
40:10
whether
40:10
that's
40:10
a
40:10
data
40:10
team
40:11
or
40:11
not,
40:11
I
40:11
didn't
40:11
check
40:11
or
40:11
clarify,
40:12
but
40:12
if
40:12
you
40:12
hand
40:12
it
40:13
off
40:13
to
40:13
just
40:13
tech
40:13
and
40:13
then
40:13
the
40:13
founder
40:14
doesn't
40:14
become
40:14
involved,
40:15
it
40:15
almost
40:15
always
40:16
fails
40:16
in
40:16
hand
40:16
to
40:16
be
40:16
redone
40:17
because
40:18
the
40:18
business,
40:18
there's
40:18
nobody
40:19
injecting
40:19
business
40:19
context.
40:20
Like,
40:20
if
40:21
you're
40:21
just
40:21
setting
40:22
up
40:22
for
40:22
an
40:22
ideal
40:22
scenario
40:23
which
40:23
may
40:23
or
40:23
may
40:23
not
40:23
exist
40:24
or
40:24
may
40:24
or
40:25
may
40:25
not
40:25
be
40:25
the
40:25
right
40:25
thing
40:26
for
40:26
any
40:27
particular
40:27
business.
40:27
Yeah,
40:28
you
40:28
get
40:28
an
40:28
expensive
40:29
Rolodex.
40:29
Yeah,
40:30
there
40:30
you
40:30
go.
40:30
That's
40:31
a
40:31
nice
40:31
way
40:31
of
40:31
putting
40:31
it.
40:32
Expensive
40:32
Rolodex
40:33
that
40:33
one
40:34
day
40:34
might
40:34
connect
40:34
into
40:35
a
40:36
warehouse
40:36
and
40:36
do
40:36
some
40:37
amazing
40:37
AI
40:37
things
40:37
for
40:38
you.
40:39
There's
40:39
agents,
40:40
though.
40:40
Don't
40:40
worry,
40:40
there's
40:40
agents.
40:41
Anyway,
40:43
I'm
40:43
showing
40:43
my
40:44
age
40:44
with
40:44
all
40:44
this
40:44
cynicism,
40:45
Dylan.
40:47
I'm
40:47
very
40:47
wary
40:48
of
40:48
it.
40:50
Tell
40:50
me
40:50
about
40:50
the
40:51
story
40:51
of
40:51
how
40:52
you
40:52
grew
40:52
the
40:52
newsletter
40:53
to
40:54
7,000
40:54
subscribers.
40:55
A
40:55
very
40:55
impressive
40:55
thing.
40:56
How
40:56
long
40:56
have
40:56
you
40:56
been
40:56
doing
40:56
it
40:57
for
40:57
and
40:58
what
40:59
data
40:59
have
40:59
you
40:59
collected
41:00
about
41:00
the
41:00
newsletter
41:01
and
41:01
about
41:01
your
41:01
subscribers
41:02
and
41:02
potential
41:02
subscribers
41:03
along
41:03
the
41:03
way?
41:03
This
41:03
enabled
41:04
you
41:04
to
41:04
be
41:04
so
41:04
successful
41:05
with
41:05
it.
41:05
So
41:06
I
41:06
launched
41:06
a
41:06
newsletter
41:07
last
41:07
April.
41:09
I
41:09
kind
41:09
of
41:09
built
41:09
up
41:09
to
41:10
it.
41:10
I
41:10
got
41:11
head
41:11
start,
41:12
wrote
41:12
like
41:12
at
41:12
least
41:13
four
41:13
or
41:13
five
41:13
articles,
41:14
said
41:14
okay,
41:14
this
41:14
can
41:15
be
41:15
a
41:15
weekly
41:15
thing,
41:15
I'm
41:16
going
41:16
to
41:16
give
41:16
it
41:16
five
41:16
minutes.
41:17
It
41:17
is
41:17
not
41:18
kept
41:18
five
41:18
minutes.
41:18
It's
41:18
usually
41:19
now
41:19
between
41:19
10
41:19
and
41:19
15
41:20
minutes.
41:20
But
41:20
that's
41:20
because
41:21
trying
41:21
to
41:21
explain
41:22
each
41:22
data
41:22
domain
41:23
takes
41:24
its
41:24
toll
41:24
and
41:24
takes
41:25
its
41:25
time.
41:27
But
41:27
I
41:27
really
41:28
kind
41:28
of
41:29
leveraged
41:29
what
41:29
I
41:29
had
41:30
built
41:30
on
41:30
LinkedIn
41:31
and
41:33
kind
41:33
of
41:34
I
41:34
share
41:35
now
41:35
all
41:35
my
41:35
LinkedIn
41:36
content
41:36
and
41:37
full
41:38
story
41:38
is
41:38
I've
41:39
been
41:39
on
41:39
LinkedIn
41:39
since
41:40
kind
41:40
of,
41:41
I
41:41
think
41:42
January
41:43
22nd.
41:44
So
41:44
it's
41:44
been
41:44
over
41:45
three
41:45
years
41:45
now.
41:45
And
41:46
after
41:47
a
41:47
couple
41:47
of
41:47
years
41:47
I
41:48
was
41:48
really
41:49
tired
41:49
of
41:49
LinkedIn
41:49
because
41:50
I
41:50
mean
41:50
LinkedIn's
41:50
great,
41:51
but
41:51
you're
41:51
just
41:51
sharing
41:52
short
41:52
quitbit
41:53
stuff
41:53
and,
41:54
and
41:55
the
41:55
stuff
41:55
that
41:55
does
41:55
really
41:56
well
41:56
on
41:56
LinkedIn,
41:57
it
41:57
doesn't
41:57
really
41:58
add
41:58
value
41:58
anymore.
41:59
Like
42:00
you
42:00
see
42:00
so
42:00
many
42:00
selfie
42:01
pictures
42:01
or
42:02
like
42:02
random
42:03
stuff
42:03
about
42:03
people's
42:04
personal
42:04
lives
42:04
and
42:04
you're
42:05
like,
42:05
that
42:05
doesn't
42:05
really
42:06
have.
42:06
Well,
42:06
it's
42:06
not
42:06
educational.
42:07
And
42:08
I
42:08
was
42:08
kind
42:08
of
42:08
getting
42:09
tired
42:09
of
42:09
that.
42:09
I'm
42:09
like,
42:09
I
42:10
want
42:10
to
42:10
write
42:10
something
42:11
about
42:12
what
42:12
is
42:12
data
42:13
strategy
42:13
or
42:13
what
42:13
is
42:14
data
42:14
engineering,
42:15
what
42:15
does
42:15
it
42:15
mean,
42:15
why
42:15
do
42:16
people
42:16
care
42:16
about
42:16
it?
42:16
And
42:17
I
42:17
want
42:17
to
42:17
learn
42:18
about
42:18
it
42:18
too
42:18
in
42:18
the
42:18
process.
42:19
So
42:19
that's
42:19
why
42:19
I
42:19
launched
42:20
my
42:20
newsletter.
42:21
And
42:22
when
42:23
I
42:23
launched
42:23
it
42:24
I
42:24
leveraged
42:24
LinkedIn
42:25
so
42:25
I
42:25
share
42:26
kind
42:26
of
42:27
my
42:27
different
42:27
infographics
42:28
on
42:28
LinkedIn
42:29
and
42:29
then
42:30
kind
42:30
of
42:30
pieces
42:31
from
42:31
the,
42:33
from
42:33
the
42:33
article.
42:34
So
42:35
it
42:35
actually
42:36
my
42:37
long
42:37
form
42:37
content
42:37
now
42:38
drives
42:38
all
42:38
my
42:38
short
42:39
form
42:39
content
42:39
and
42:40
I
42:40
don't
42:40
have
42:40
to
42:40
create
42:40
new
42:41
posts
42:41
for
42:41
LinkedIn
42:41
so
42:42
I,
42:42
it
42:43
helps
42:43
in
42:43
that
42:43
way.
42:44
And
42:44
I
42:45
think
42:45
just
42:45
kind
42:45
of
42:45
that
42:46
exposure
42:46
on
42:46
LinkedIn
42:48
has,
42:48
has
42:48
built
42:49
up
42:49
the
42:49
newsletter
42:49
people
42:50
see
42:50
and
42:51
finally
42:51
realize
42:52
that
42:52
oh,
42:52
this
42:53
isn't
42:53
just
42:53
made
42:53
for
42:53
LinkedIn,
42:54
this
42:54
is
42:54
actually
42:54
for
42:55
from
42:55
a
42:55
newsletter.
42:55
Oh,
42:56
this
42:56
is
42:56
actually
42:56
a
42:56
long
42:56
form
42:56
piece.
42:57
Oh,
42:57
this
42:57
is
42:57
interesting.
42:57
I'm
42:58
going
42:58
to
42:58
read
42:58
it
42:58
all.
42:59
That
42:59
has
42:59
kind
42:59
of
43:00
built
43:00
the
43:00
following
43:01
from
43:02
what
43:02
it
43:02
was
43:02
zero
43:03
and
43:03
over
43:04
a
43:04
year
43:04
ago
43:04
and
43:04
now
43:04
it's
43:05
about
43:05
7,500.
43:07
And
43:08
I
43:08
think
43:09
the
43:09
thing
43:10
that
43:10
I've
43:11
really
43:11
taken
43:11
away
43:11
from
43:11
it
43:12
is
43:12
a
43:12
lot
43:12
of
43:12
people
43:12
can
43:12
launch
43:13
a
43:13
newsletter
43:13
and
43:13
everybody
43:14
has
43:14
nowadays
43:17
you
43:18
have
43:18
to
43:18
kind
43:18
of
43:19
make
43:19
sure
43:19
it
43:20
has
43:20
a
43:20
niche
43:20
and
43:21
it
43:21
has
43:21
a
43:22
certain
43:22
level
43:22
of
43:22
quality
43:23
to
43:23
it
43:23
to
43:24
do
43:24
well,
43:25
and
43:25
that's
43:26
where
43:26
I've
43:26
really
43:26
kind
43:27
of
43:27
put
43:27
my
43:27
foot
43:27
down.
43:28
Like,
43:28
I
43:28
want
43:28
to
43:29
make
43:29
sure
43:29
it's
43:29
a
43:29
certain
43:30
quality
43:30
point
43:31
for
43:31
me
43:31
to
43:32
put
43:32
out.
43:33
Otherwise
43:33
I'm
43:33
not
43:34
going
43:34
to
43:34
put
43:34
it
43:34
out.
43:35
And
43:36
I
43:36
think
43:37
that
43:37
has
43:37
helped
43:38
the
43:38
growth
43:38
because
43:38
people
43:39
recognize,
43:39
okay,
43:40
this
43:40
is,
43:41
this
43:41
is
43:41
really
43:41
explaining
43:42
a
43:42
problem
43:42
that
43:42
I
43:43
see
43:43
or
43:43
I
43:44
don't
43:44
quite
43:44
understand.
43:46
And
43:47
there
43:47
are
43:48
still
43:48
a
43:48
lot
43:48
of
43:48
people
43:48
who
43:50
comment
43:50
to
43:50
me
43:51
in
43:51
person.
43:51
They're
43:51
like,
43:51
oh,
43:52
I
43:52
really
43:52
love
43:52
your
43:52
LinkedIn
43:53
post.
43:53
Like,
43:53
the
43:53
diagrams
43:54
are
43:54
so
43:54
interesting.
43:54
I'm
43:55
like,
43:55
do
43:55
you
43:55
know
43:55
those
43:55
come
43:56
from
43:56
a
43:56
newsletter?
43:56
They're
43:56
like,
43:56
no,
43:57
I
43:57
had
43:57
no
43:57
idea.
43:57
I'm
43:58
like,
43:58
oh,
43:58
come
43:59
on.
44:00
With
44:00
even
44:00
fuller
44:00
explanations
44:01
and
44:01
even
44:01
better.
44:02
Diagrams,
44:03
you
44:03
can
44:03
read
44:03
the
44:04
whole
44:04
article
44:04
on
44:04
it.
44:04
There's
44:05
a
44:05
lot
44:05
more,
44:06
but
44:07
it's
44:07
been
44:07
great.
44:08
I've
44:08
really
44:08
enjoyed
44:09
it.
44:09
I've
44:09
learned
44:10
a
44:10
lot
44:10
about
44:10
different
44:10
data
44:11
domains
44:11
and
44:11
how
44:11
they
44:12
cut
44:12
across
44:12
to
44:12
one
44:12
another.
44:13
And
44:13
I
44:13
think
44:14
to
44:14
what
44:14
you
44:14
said
44:14
earlier,
44:15
there
44:15
might
44:15
be
44:15
a
44:15
book
44:16
coming
44:16
out
44:16
at
44:16
some
44:16
point
44:17
that
44:17
kind
44:18
of
44:18
brings
44:18
it
44:18
all
44:18
together.
44:18
And
44:19
that's
44:19
really
44:19
my
44:19
end
44:19
goal.
44:20
This
44:20
is
44:20
to
44:21
bring
44:21
together
44:21
the
44:22
data
44:22
ecosystem
44:23
into
44:24
one
44:24
book.
44:25
And
44:25
I've
44:26
definitely
44:26
written
44:26
enough
44:27
words
44:27
from
44:28
the
44:28
newsletters.
44:29
So
44:29
it's
44:29
going
44:29
to
44:29
be
44:30
a
44:30
heck
44:30
of
44:30
a
44:31
time
44:32
editing
44:32
that
44:32
and
44:33
bringing
44:33
it
44:33
together
44:33
and
44:34
kind
44:34
of
44:34
probably
44:34
updating
44:35
it
44:35
and
44:35
synthesizing
44:36
that.
44:36
But
44:36
I
44:36
think
44:37
it's,
44:38
it's
44:38
something
44:38
that
44:39
doesn't
44:39
exist
44:39
out
44:39
there.
44:40
There's
44:40
no
44:40
book
44:40
out
44:41
there
44:41
that's
44:41
like,
44:41
this
44:41
is
44:42
what
44:42
data
44:42
is
44:43
and
44:43
this
44:43
is
44:43
how
44:44
to
44:44
think
44:44
about
44:44
it
44:44
and
44:44
why
44:45
it
44:45
matters.
44:46
An
44:46
overall
44:47
kind
44:47
of
44:47
perspective.
44:48
So
44:49
yeah,
44:50
that's
44:50
my,
44:50
that's
44:51
my
44:51
long
44:51
winded
44:51
rant
44:52
on
44:52
that.
44:52
First
44:53
on
44:53
the
44:53
list
44:53
for
44:53
an
44:53
autographed
44:54
pre
44:54
order
44:54
copy
44:55
of
44:55
that
44:55
one.
44:55
I
44:56
got
44:56
you.
44:56
I
44:56
got
44:56
you.
44:58
I
44:58
love
44:59
it.
44:59
And
44:59
there's
44:59
an
44:59
interesting
45:00
data
45:00
point
45:00
as
45:00
well
45:00
that
45:00
I've
45:00
observed.
45:03
You
45:03
know,
45:03
I
45:03
have
45:04
a
45:04
newsletter
45:04
that
45:04
I
45:06
pull
45:07
out
45:07
of
45:07
this
45:07
podcast.
45:08
Like
45:08
this
45:08
is
45:08
my
45:09
long
45:09
form
45:09
content
45:10
right
45:10
here.
45:10
Right.
45:13
And
45:13
I
45:13
love
45:14
doing
45:14
it
45:14
because
45:14
I
45:15
find
45:15
it
45:15
easier
45:15
to
45:15
speak
45:15
than
45:16
I
45:16
do
45:16
to
45:16
write.
45:17
Although
45:17
tools
45:17
like
45:17
Whisper
45:18
Flow
45:18
make
45:18
that
45:19
easier
45:20
in
45:20
any
45:20
format
45:21
now
45:21
as
45:21
well.
45:22
But
45:22
the
45:22
interesting
45:22
thing,
45:23
and
45:24
just
45:24
first
45:24
to
45:24
address
45:25
your
45:25
point
45:25
on
45:25
LinkedIn,
45:26
like,
45:26
people
45:26
behave
45:27
in
45:27
a
45:27
way
45:27
that
45:28
people
45:28
respond
45:28
to
45:29
what
45:29
the
45:29
algorithm
45:30
rewards.
45:31
I'm
45:32
really
45:32
interested
45:32
to
45:32
see
45:32
how
45:33
LinkedIn
45:33
takes
45:33
this
45:33
video
45:34
thread
45:34
that
45:34
it's
45:34
obviously
45:35
hitting
45:35
super
45:36
hard
45:36
right
45:36
now.
45:36
I
45:36
mean,
45:36
it's,
45:37
they've
45:37
got
45:37
all
45:37
the
45:37
marketing
45:38
people
45:38
on
45:38
there.
45:39
They
45:39
put
45:39
someone
45:39
on
45:40
Stephen
45:40
Bartlett's
45:41
podcast
45:41
just
45:42
to
45:42
Talk
45:42
about
45:42
it
45:43
like
45:43
that
45:43
was
45:43
of
45:43
course
45:44
a
45:44
fortune.
45:46
So
45:47
I'm
45:47
interested
45:47
to
45:47
see
45:47
where
45:48
it
45:48
goes
45:50
because
45:51
interestingly,
45:51
even
45:51
with
45:52
all
45:52
the
45:52
AI
45:52
technology
45:53
that
45:53
I'm
45:53
sure
45:53
LinkedIn
45:54
has
45:54
available
45:54
to
45:54
them,
45:54
it's
45:55
harder
45:55
for
45:55
them
45:55
to
45:55
understand.
45:56
Like
45:56
straight
45:56
off
45:56
the
45:56
bat,
45:57
what
45:57
if,
45:57
what
45:57
a
45:57
15
45:58
minute
45:58
talking
45:58
head
45:58
video
45:59
is
45:59
about
45:59
compared
45:59
to
45:59
a
46:00
15,
46:00
15
46:01
seconds.
46:02
Sorry,
46:02
15
46:02
second
46:02
talking
46:03
head
46:03
video
46:03
compared
46:04
to
46:04
a
46:04
15
46:04
second
46:05
post.
46:05
So
46:05
interesting
46:06
to
46:06
see
46:06
how
46:06
they,
46:06
how
46:07
they
46:07
reward
46:07
that
46:07
and
46:07
how
46:08
that
46:08
advances.
46:08
But
46:09
the
46:09
advantage
46:10
you
46:10
have
46:10
in
46:10
substack,
46:11
again,
46:11
no
46:12
surprise
46:12
here
46:12
because
46:12
it's
46:13
you
46:13
is
46:13
a
46:13
big
46:14
data
46:14
advantage
46:14
because
46:15
you
46:15
now
46:15
have
46:16
a
46:16
Super
46:17
list
46:17
of
46:18
7,500
46:19
people
46:19
and
46:19
you
46:20
own
46:20
that
46:20
email
46:20
list
46:20
and
46:21
you
46:21
can
46:21
take
46:21
that
46:21
with
46:21
you
46:21
anywhere
46:22
you
46:22
go.
46:22
Like
46:22
you
46:22
can't
46:23
even
46:23
get
46:23
your
46:24
connections
46:24
email
46:25
list
46:25
out
46:25
of
46:26
LinkedIn,
46:26
never
46:27
mind
46:27
people
46:28
who
46:28
interact
46:28
with
46:29
your
46:29
content.
46:30
So
46:30
that's
46:31
again,
46:31
credit
46:32
to
46:32
you
46:32
for
46:32
building
46:32
what's
46:33
a
46:33
super
46:33
valuable
46:33
list.
46:33
I'll
46:34
give
46:34
you
46:34
$5
46:35
for
46:35
a
46:35
copy
46:35
of
46:35
it.
46:37
Don't
46:38
worry,
46:38
I'm
46:38
not
46:38
selling
46:38
any
46:39
subscriptions.
46:39
So
46:39
if
46:40
anyone
46:40
subscribes
46:40
off
46:40
of
46:41
this,
46:41
I'm
46:42
not
46:42
going
46:42
to
46:42
bother
46:43
selling
46:43
your
46:43
email.
46:44
Just
46:45
my
46:46
attempt
46:46
at
46:46
a
46:46
bit
46:46
of
46:47
British
46:47
shock.
46:49
It's
46:49
still
46:49
in
46:49
there
46:50
somewhere.
46:50
Still
46:51
in
46:51
there
46:51
somewhere.
46:53
All
46:53
right,
46:53
so
46:53
we
46:53
covered
46:54
so
46:54
much
46:54
today.
46:54
So
46:54
we
46:54
covered
46:55
your
46:55
study.
46:56
We'll
46:56
start
46:56
to
46:56
see
46:56
that
46:57
come
46:57
out
46:57
in
46:57
diagram
46:58
form
46:58
and
46:58
newsletter
46:58
form
46:59
as
46:59
we
46:59
go
46:59
on.
47:00
We've
47:00
covered
47:01
the
47:01
importance
47:01
of
47:01
connecting
47:02
data
47:02
to
47:02
the
47:03
business
47:03
strategy
47:03
and
47:03
I
47:03
know
47:04
you
47:04
said
47:04
all
47:04
those
47:04
leaders
47:04
had
47:05
that
47:05
in
47:05
common,
47:05
but
47:05
so
47:05
many
47:06
folks
47:06
don't
47:06
do
47:06
it.
47:07
So
47:08
you
47:08
know,
47:08
you
47:09
have
47:09
my
47:09
commitment
47:09
to
47:10
keep
47:11
treading
47:11
the
47:12
good
47:12
path
47:13
and
47:13
providing
47:13
high
47:14
value
47:14
data
47:14
data
47:15
consultancy
47:15
and
47:15
analytics
47:16
consultancy
47:16
out
47:16
there.
47:18
Along
47:18
the
47:18
way
47:18
we've
47:19
learned
47:20
how
47:21
and
47:21
you've
47:21
definitely
47:21
got
47:22
some
47:22
amazing
47:23
British
47:23
humility
47:24
going
47:24
on
47:24
there.
47:24
Like
47:24
building
47:24
a
47:25
newsletter
47:25
to
47:25
7,500
47:26
in
47:26
just
47:26
over
47:26
a
47:27
year
47:27
is
47:27
a
47:27
spectacular
47:28
achievement.
47:28
So
47:30
it
47:30
deserves
47:30
all
47:31
the,
47:31
you
47:31
know,
47:32
all
47:32
the
47:32
credit.
47:32
And
47:32
folks
47:33
can
47:33
find
47:33
the
47:34
data
47:34
ecosystem
47:34
newsletter
47:35
and
47:35
substack
47:35
as
47:36
I
47:36
hopefully
47:36
point
47:36
them
47:36
towards
47:38
and
47:38
find
47:38
you
47:38
on
47:39
LinkedIn.
47:39
But
47:41
so
47:41
we
47:41
covered
47:41
so
47:41
much
47:41
today
47:42
and
47:42
really
47:42
grateful
47:42
for
47:43
you
47:43
coming
47:43
on.
47:43
I
47:43
look
47:44
forward
47:44
to
47:44
getting
47:44
the
47:45
industry
47:45
report
47:45
when
47:46
you
47:46
put
47:46
it
47:46
out
47:46
from
47:46
all
47:47
those
47:47
interviews
47:48
and
47:48
seeing
47:48
what
47:48
you
47:48
share
47:49
from
47:49
that
47:49
is
47:50
the
47:51
where
47:52
else
47:52
can
47:52
folks
47:52
find
47:52
you?
47:53
What
47:53
should
47:53
folks
47:53
look
47:53
out
47:54
for?
47:54
What's
47:54
your
47:55
one
47:55
hope
47:55
and
47:55
dream
47:55
for
47:56
the
47:56
future
47:56
of
47:56
data
47:57
by
47:58
means
47:58
of.
47:58
Signing
47:58
off
47:59
where
47:59
people
47:59
can
47:59
find
48:00
me.
48:00
So
48:00
thanks
48:00
for
48:00
all
48:00
that.
48:01
Yeah,
48:01
good
48:02
wrap
48:02
up
48:02
as
48:02
well.
48:03
Where
48:03
folks
48:04
can
48:04
find
48:04
me
48:04
is,
48:04
is
48:05
LinkedIn
48:05
and
48:05
Substack.
48:08
Those
48:08
are
48:08
my
48:08
only
48:08
two
48:09
channels.
48:09
I
48:09
don't
48:09
have
48:09
time
48:10
for
48:10
Twitter.
48:10
I
48:11
hate
48:11
Instagram,
48:12
I
48:12
don't
48:12
use
48:13
Facebook,
48:14
and
48:14
I
48:15
would
48:15
like
48:15
to
48:15
use
48:16
media
48:16
more,
48:16
but
48:16
I
48:16
just
48:16
don't
48:17
have
48:17
time
48:17
to
48:17
pour
48:18
everything
48:18
across
48:19
maybe
48:19
one
48:19
day.
48:20
And
48:20
then
48:20
I
48:20
also
48:20
don't
48:21
use
48:21
YouTube
48:21
because
48:21
I
48:22
don't
48:22
like
48:22
going
48:22
on
48:23
camera
48:23
or
48:23
posting
48:24
selfies.
48:24
Um,
48:25
so
48:27
I'm
48:27
fine
48:27
for.
48:27
Fine
48:28
for
48:28
the
48:28
odd
48:28
podcast
48:29
and
48:29
everything.
48:29
But
48:30
I'm
48:30
even
48:30
more
48:31
grateful
48:31
for
48:31
you
48:31
coming
48:31
on.
48:33
No,
48:33
yeah,
48:34
but
48:34
the
48:34
data
48:34
ecosystem
48:35
on
48:35
Substack
48:36
is
48:36
my
48:36
main,
48:36
main
48:36
thing
48:37
where,
48:37
where
48:37
my
48:37
main
48:37
thought
48:38
leadership
48:38
content
48:39
is
48:39
coming
48:39
out.
48:40
And
48:40
what
48:40
do
48:41
I
48:41
hope
48:41
for
48:41
the
48:42
future
48:42
of
48:42
data?
48:42
That's
48:43
a.
48:43
That's
48:43
a
48:43
great
48:43
question.
48:44
I
48:44
think
48:45
what
48:45
I
48:45
hope
48:45
for
48:46
is
48:47
people
48:47
to
48:47
just
48:48
be
48:48
more
48:48
strategic
48:49
about
48:49
it
48:49
and
48:49
to
48:49
think
48:49
more
48:50
about
48:50
the
48:50
big
48:50
picture
48:50
and
48:51
to
48:51
think
48:51
more
48:51
holistically
48:52
because,
48:52
like,
48:54
I'm
48:54
going
48:54
to
48:54
get
48:54
cynical
48:55
quite
48:56
soon
48:56
just
48:56
based
48:56
off
48:57
how
48:57
many
48:57
mistakes
48:58
we
48:58
are
48:58
constantly
48:59
remaking
48:59
and
49:00
making
49:00
over
49:00
again
49:00
and
49:00
making
49:01
over
49:01
again.
49:01
And
49:02
AI
49:02
is
49:02
not
49:02
going
49:03
to
49:03
be
49:03
the
49:03
aha
49:03
moment.
49:04
It's
49:04
going
49:04
to
49:04
take
49:04
a
49:04
while
49:05
for
49:05
us
49:05
to
49:05
get
49:05
there.
49:07
And
49:08
so
49:08
we'll
49:08
see,
49:09
we'll
49:09
see
49:09
when
49:09
that
49:10
happens.
49:10
But
49:10
I
49:10
don't
49:10
think
49:11
it's
49:11
going
49:11
to
49:11
happen
49:11
anytime
49:12
soon.
49:12
I
49:12
guess
49:12
if
49:12
it
49:12
does
49:13
happen,
49:13
I'm
49:13
probably
49:13
out
49:13
of
49:13
a
49:14
job,
49:14
so
49:14
maybe
49:14
I
49:14
don't
49:15
want
49:15
it
49:15
to
49:15
happen
49:15
so
49:16
much.
49:17
Well,
49:17
you
49:17
know,
49:18
you
49:18
and
49:18
everybody
49:18
else.
49:19
Right,
49:19
you
49:19
and
49:19
everybody
49:20
else.
49:21
Exactly.
49:22
Yeah.
49:22
Thanks
49:22
so
49:22
much
49:22
for
49:23
coming
49:23
on.
49:23
Keep
49:23
rocking
49:23
it,
49:23
Dylan.
49:25
I
49:25
love
49:25
the.
49:26
I'll
49:26
go
49:26
have
49:27
a
49:27
look
49:27
at
49:27
Escalidraw
49:28
now
49:28
and
49:29
I'll
49:29
keep
49:29
enjoying
49:29
the
49:30
newsletter
49:30
and,
49:30
you
49:30
know,
49:30
while
49:31
you
49:31
keep
49:31
going
49:31
to
49:31
four
49:31
data
49:32
events
49:32
every
49:32
week,
49:33
it's
49:33
only
49:33
a
49:33
matter
49:33
of
49:33
time
49:34
before
49:34
we
49:34
have
49:34
to
49:34
cross
49:34
paths
49:35
in
49:35
person.
49:35
So
49:35
I
49:35
will
49:36
look
49:36
forward
49:36
to
49:37
that
49:37
day
49:37
whenever
49:37
it
49:37
arrives.
49:38
Yeah,
49:38
perfect.
49:39
Thanks
49:39
so
49:39
much,
49:39
Graham.
49:39
It's
49:40
been
49:40
great.
49:40
All
49:40
right,
49:41
take
49:41
care.
49:41
Bye
49:41
Bye.
49:42
Thanks
49:42
for
49:42
tuning
49:42
in
49:43
to
49:43
Transformed
49:43
with
49:44
Data.
49:44
If
49:45
today's
49:45
conversation
49:46
gave
49:46
you
49:46
even
49:46
one
49:46
insight,
49:47
one
49:47
aha
49:48
moment,
49:48
or
49:48
one
49:48
new
49:49
idea
49:49
to
49:49
take
49:49
action
49:50
on,
49:50
do
49:50
me
49:51
a
49:51
favor.
49:51
Subscribe,
49:52
leave
49:53
a
49:53
review,
49:53
and
49:53
share
49:53
this
49:54
with
49:54
someone
49:54
who's
49:54
ready
49:54
to
49:55
level
49:55
up.
49:55
Until
49:56
next
49:56
time,
49:57
keep
49:57
asking
49:57
the
49:57
right
49:57
questions,
49:58
keep
49:59
challenging
49:59
the
49:59
status
50:00
quo,
50:00
and
50:00
keep
50:01
transforming
50:01
with
50:01
Data.