►
From YouTube: Latest on Microsoft Graph Data Connect datasets
Description
In this 14-minute developer focused demo – Nik Charlebois reviews REST APIs, Connectors and Data Connect that make up the Graph Ecosystem. Data Connect enables bulk data access for insights and analytics. Data is stored in Azure Data Factory or Azure Synapse. Reviewed 9 data sets recently released, 2 more to be released soon and 7 in the Backlog. Briefly covered Azure Synapse integration and quick demo of the Synapse Copy Data Tool (wizard). This PnP Community demo is taken from the weekly Microsoft 365 Platform Community call recorded on April 19, 2022.
Demo Presenter
• Nik Charlebois (Microsoft) | @NikCharlebois
Supporting materials
General
• Documentation – Graph Data Connect Policies | https://docs.microsoft.com/graph/data-connect-policies#billing-for-microsoft-graph-data-connect
• Repo – Graph Data Connect Solutions | https://github.com/microsoftgraph/dataconnect-solutions/tree/main/solutions
• Documentation - Quickstart: Use the Copy Data tool in the Azure Data Factory Studio to copy data | https://docs.microsoft.com/azure/data-factory/quickstart-create-data-factory-copy-data-tool
Site Collection Level
• Article - View usage data for your SharePoint site | https://support.microsoft.com/topic/2fa8ddc2-c4b3-4268-8d26-a772dc55779e
• Documentation - View search usage reports in modern sites | https://docs.microsoft.com/sharepoint/view-search-usage-reports-modern-sites
Tenant Admin Level
• Documentation – Microsoft 365 Reports in the admin center - SharePoint site usage | https://docs.microsoft.com/microsoft-365/admin/activity-reports/sharepoint-site-usage-ww
• Documentation - Microsoft 365 usage analytics | https://docs.microsoft.com/microsoft-365/admin/usage-analytics/usage-analytics
Via Microsoft Graph
• Documentation - SharePoint site usage reports | https://docs.microsoft.com/graph/api/resources/sharepoint-site-usage-reports
Learn more
• Microsoft 365 Unified Sample gallery - https://aka.ms/m365/samples
• Microsoft 365 Platform Community in YouTube - https://aka.ms/m365/videos
• Microsoft 365 Platform Community - http://aka.ms/m365pnp
A
All
right
so
quick
update
on
the
the
data
sets
for
microsoft
gravity.connect
before
we
actually
dive
into
what's
new.
With
regards
to
the
dataset,
I
just
want
to
do
a
quick
overview
of
the
different
components
of
what
makes
the
microsoft
graph
ecosystem
right.
The
first
component
is
something
that
I
think
we're
all
used
to,
which
is
the
rest.
Apis
they've
been
around
for
many
years.
Those
allow
for
crowd
type
scenarios
right,
transactional
scenarios
where
you
can
go
and
create
read,
update,
delete
data
inside
of
microsoft
365..
A
They
are,
however,
throttled
which
means
they're
not
built
for
large
data
exports.
If
you
want
right,
because
you
only
have
a
certain
limitation
of
how
much
data
you
can
get
in
a
in
a
certain
time
frame,
the
second
component
is
the
connectors,
so
connectors
are
built
to
ingest
data
inside
of
microsoft
graph,
to
bring
your
on-premises
data
inside
of
the
microsoft
graph
to
allow
you
to
build
search,
related
scenarios
to
just
improve
the
experience.
A
The
overall
experience,
let's
say
on
the
off
portal,
the
office.com
and
so
on,
and
then
the
third
piece,
which
is
really
the
focus
of
this
session
here-
is
microsoft.
Graph
data
connect,
which
is
really
built
to
allow
bulk
data
accessed,
to
generate
your
own
insights
and
analytics
over
a
period
of
time
right.
So
when
you're
using
microsoft
graph
data
connect,
there
is
an
azure
plane
which
means
that
the
data
that
you're
exporting
will
be
exported
into
azure,
using
either
azure
data
factory
or
azure
synapse,
and
this
is
something
I
want
to
touch
on.
A
I
know
the
focus
is
really
more
on
what's
new
with
data
sets,
but
I
want
to
leave
time
at
the
end
to
just
introduce
the
new
support
we
have
for
azure
synapse
and
the
advantage
of
using
microsoft.
Draft
data
connect.
Well,
the
first
one
is
you're
not
going
to
be
subject
to
throttling,
so
it
can
extract
a
large
amount
of
data
without
hitting
any
troubling
limits
right.
So
you
can
extract
millions
and
millions
of
emails.
For
example,
calendar
invites
if
you
want
to
be
able
to
generate
your
own
insights.
A
The
other
advantage
is
you
can
scope
it
down
to
an
audience
you
can
say.
I
only
want
to
get
the
information
for
people
that
are
part
of
the
legal
and
hr
team,
for
example,
and
the
third
thing
is,
you
can
actually
scope
it
down
at
the
field
level.
So,
for
example,
if
you
want
to
go
and
generate
insights
to
understand
how
people
are
collaborating
via
email
inside
of
your
organization,
you
don't
want
to
extract
the
body
of
the
email.
You
don't
want
to
go
and
extract
the
attachments
right.
You
don't
care
about
that.
A
That's
all
I
care
about
and
that
will
honor
the
data
contract
and
extract
the
data
inside
of
an
azure
storage
account
that
only
contains
the
selected
fields
and
very
important,
and
the
data
will
be
stored
as
json,
so
you
can
go
in
and
load
it
directly
within
power
bi
or
you
can
just
use
something
like
azure
synapse
to
build
your
extract,
transform
load
pipelines,
quick
update
on
the
data
sets.
Now
I
need
to
talk
about
the
legend
here:
okay,
so
items
that
are
in
black
and
the
currently
available
column.
A
These
are
items
that
have
been
available
for
for
months
right.
These
are
items
that
we've
had
since
almost
the
beginning
of
microsoft.
Graph
data
connect
items
that
are
in
green
are
items
we've
recently
re
released,
meaning
that
in
the
past
two
to
three
months,
these
are
new
data
sets
that
we
made
available
the
ones
that
have
an
asterisk
beside
they're
currently
available
in
private
preview,
but
are
going
to
be
released
within
the
next
few
weeks
for
general
availability.
A
So,
let's
quickly
glance
through
the
new
items
in
here
right,
one
of
the
things
we
are
working
on
is
to
bring
group
conversations
to
the
forefront
being
able
to
extract
information
about
groups.
Conversation
that
you
have
in
outlook.
The
second
one
that
we
released
about,
I
would
say
two
months
ago,
is
the
inbox
data
set.
Now
you
might
have
question
around
all
right
so
looks
like
we
have
the
messages
which
is
the
email.
We
have
the
sent
items,
and
now
we
have
inbox.
What's
the
difference
between
them
all
well,
it
depends
on
your
scenario.
A
So
what
we're
trying
to
do
is
make
it
as
easy
as
possible
for
you
to
reduce
the
overall
number
of
items
that
you're
extracting
right
to
make
it
easier
to
build
your
insights
based
on
your
own
scenario,
so
the
messages
data
set
includes
everything
emails
that
have
been
sent.
Emails,
you've,
received
and
doesn't
really
matter
in
what
folder
you've
actually
stored
your
your
messages,
it's
all
the
emails,
the
sent
item
well,
that
one's
fairly
easy
it's
the
emails
you've
been
sending
right,
so
that
will
normally
help
you
remove
duplicates.
A
So,
for
example,
if
I'm
sending
an
email
right
now
to
five
of
my
colleagues,
that
will
actually
count
as
six
emails
right,
one
for
each
recipient
plus
one
for
me,
but
if
I'm
only
interested
in
knowing
how
people
are
using
emails
internally,
then
sent
item
will
help
reduce
that
overall
data
set
that
you're
going
to
be
extracting
inbox
on
the
other
end
is
really
just
the
emails
that
you
have
in
your
root
inbox,
folder
very
important.
Now,
let's
talk
about
the
the
new
groups,
data
set
that
we've
released,
so
we
released
three
new
groups.
A
Data
set
the
group
details
which
contains
information
about
like
is
this
a
public
or
a
private
group?
Is
this
a
ml
enabled
right?
So
it's
really
more
around
the
configuration
of
the
groups,
the
group
members
and
the
group
owners.
One
thing,
that's
really
important
to
note,
is
with
microsoft,
graph
data
connect.
The
data
sets
are
normally
metered,
meaning
that
you're
going
to
be
charged
per
thousand
items
that
you
extract
everything
that
is
beside
azure
id
and
here
those
are
all
free
data
sets
as
well
as
the
data
sets,
while
they're
in
preview.
Okay.
A
A
Let's
move
on
to
teams
right,
so
we
are
we
just
released
last
week,
the
private
preview
for
call
records
call
records,
contain
information
about
who's,
been
joining
the
meeting
for
how
long
was
the
meeting
and
then
how
well
pretty
much
information
about
when
was
the
meeting
started?
When
was
it
ended?
A
We
have
information
about
channel
details
right.
That
is
also
in
preview,
essentially
information
about
all
right,
so
this
channel
is
a
private
channel.
We
have
giffies
enabled
we
have
right.
So
all
the
settings
for
the
different
channels,
chats
we've
had
that
for
a
long
time
now.
Those
are
private
chat,
so
one-on-one
in
group
chat
and
we've
also
released
a
private
preview
for
the
standard
channel
conversation
right.
What
we
mean
by
standard
here
is
that
we
still
don't
support
private
channels.
Those
are
just
standard
channels.
A
On
the
sharepoint
front,
we
have
a
document
sharing
information
data
set
which
contains
information
about
all
the
sites,
all
the
lists
and
all
the
items
in
your
sharepoint
online
environment,
along
with
information
about
the
users.
It's
the
the
document
or
the
item
is
shared
with
right.
So
it'll
tell
you,
for
example,
all
right,
so
this
file
here
is
shared
with
20
people,
and
five
of
them
are
external
users,
for
example.
A
So
you
can
actually
build
dashboards
around
this,
and
this
is
one
I
want
to
bring
up
here
just
to
do
some
quick
ideation,
but
essentially
one
of
the
demos
we
built
right
was
just
quickly
understand
all
right.
So
how
are
documents
being
shared
externally
right?
So,
for
example,
here
these
are
all
documents
that
have
been
shared
with
external
users
on
my
hr
site,
so
I
can
go
in
and
have
a
look
here
and
say:
yeah
all
right.
So
there's
this
document
called
staff
personalization
or
there's.
A
A
Another
type
of
visualization
we
could
create
is
try
to
understand
right.
What
are
the
top
externally
shared
files
right
so,
for
example,
here
this
dot,
this
pdf
document
is
shared
with
19
external
users
right
like
what's
in
there.
Why
is
it
like
so
popular,
and
why
is
it
shared
that
often
with
external
users
same
goes
for
the
over
shared
sites
right
like
what
share
what
sites
are
being
overshared,
so
there's
this
site
here
right,
ceo
connection,
shared
with
63
users
right,
maybe
this
is
something
we
actually
want
to
fly
and
investigate
like.
A
Why
is
this
site
here?
That
should
be
limited
to
the
ceo's
organization
shared
with,
so
many
users
try
to
understand
as
well
how
people
are
using
sharing
links
inside
of
the
organization
right
so
right
now
I
can
see
that
there
were
210
links
generated
that
could
be
shared
with
anyone
inside
of
my
organization,
whereas
I
only
have
about
23
that
were
shared
with
specific
people.
Maybe
there's
some
training
that
I
need
to
do
with
regards
to
this
ralph.
I
just
saw
your
question.
A
So
if
you
go
to
the
azure
page
search
for
microsoft,
graph
data
connect,
all
the
information
around
the
pricing
is-
is
listed
there
as
well
groups
right,
real,
quick
right,
try
to
understand
all
right.
So
how
are
we
creating
groups
based
on
the
visibility
right?
57
of
all,
our
groups
are
created
as
private
right.
What
groups
are
male
enabled?
Overall,
I
mean
these
are
just
really
really
basic
insights
that
you
could
create
right,
understand
how
people
are
actually
creating
groups
over
time
and
then
drill
down
into
the
actual
days
during
the
month.
A
Team
call
records.
Try
to
understand
like
all
right
here
are
all
the
meetings
over
time
and,
of
course
this
is
a
tenant.
The
tenant
I
use,
have
very
limited
data,
but
try
to
understand
like
how
are
people
making
having
meetings
during
the
day
right
are
these
ad
up
meetings,
meaning
that
somebody
actually
just
ping
you
on?
I
am
and
called
you
directly
are
those
scheduled
meetings
very
important.
You
can
see
that
in
my
environment
here,
even
though
I
have
very
a
limited
set
of
meetings,
60s,
almost
67
percent
of
them
were
adopt
meetings
right.
A
That
in
some
organization
can
be
a
productivity
killer.
So
try
to
understand
this
average
time
spent
per
users
in
meetings
right.
You
can
see
that
I'm
spending
about
150
minutes
on
a
weekly
basis
in
meetings
the
average
length
of
meetings
in
my
organization
right.
So
those
are
just
some
insights
you
can
actually
generate
using
the
the
various
data
sets
that
that
we
offer
now
as
far
as
data
sets
that
are
soon
to
be
released.
A
Meeting
transcripts
is
one
of
the
big
ones
right,
so
just
as
an
ideation
imagine
being
able
to
just
do
some
cognitive
services
against
the
meeting
transcript
to
highlight
some
of
the
action
items
that
were
discussed
right.
That
is
one
thing
that
will
also
include
information
around
when
people
join
what
reaction
people
had
right.
Like
did?
We
have
thumbs
up
when
we
mentioned
a
specific
topic
when
we
mentioned
microsoft,
graph
data
connect
data
set
updates.
A
How
many
thumbs
up
did
we
get
right
being
able
to
do
that
analysis
as
well
usage
around
sharepoint
understanding
how
people
are
using
files
when
they're
creating
files,
the
leaving
files
moving
files
and
then
on
the
backlog?
We
have
plans
to
bring
into
microsoft
draft
data
connect
information
around
things
like
call
quality
data,
right,
private
and
shared
channels.
A
Of
course,
this
is
one
that
we
need
to
bring
since
we
have
standard
channel
information
around
files
and
list
items
in
sharepoint,
so
the
metadata
around
those
files
we're
looking
at
opportunities
to
bring
in
some
of
the
yammer
information
as
well
right,
community
details,
conversation
so
on
outlook
task
and
then
anything
that
is
exposed
through
a
get
in
microsoft.
Graph
is
a
potential
candidate
to
be
brought
over
to
microsoft,
graph
data,
real
quick.
I
want
to
talk
about
azure
synapse
integration
right.
A
So,
as
I
mentioned,
we
recently
introduced
support
for
azure
synapse
analytics,
which
means
directly
within
the
synapse.
You
can
go
in
and
create
pipelines
that
will
allow
you
to
extract
your
microsoft,
365
data
using
microsoft,
graph
data
connect
and
then
from
there
you
can
like
do
all
transformation.
You
want.
You
can
use
a
no
code
approach
using
like
data
flows.
You
can
use
your
your
spike.
Your
spark
run
books
if
you
want
to
do
a
bit
more
coding.
A
So
really
everything
is
baked
in
the
synapse
workspace
and
just
as
a
and
one
thing
we've
heard
is
that
it
is
challenging
for
some
people,
some
people
that
never
played
with
synapse
or
azure
data
factory
to
get
started.
So
one
thing
that
we
have
been
working
on
and
we're
working
on
improving
is
this
new
copy
data
wizard,
which
allows
you
with
a
single
click
to
just
go
and
automatically
build
a
pipeline
to
extract
your
data,
so
I
can
go
in
and
say
I
want
to
run
it
once.
A
I
want
to
run
it
on
a
daily
basis
on
a
monthly
basis.
Click
next
on
this
I'll,
just
select
my
office,
365
connection
and
then
it'll
list.
All
the
data
stats
that
I
have
available.
One
thing
we
are
working
on
is
improving
directly
the
inline
documentation
around
all
right.
So
that's
good!
You
have
the
contact
data
set,
but
what
does
it
contain
right?
So
we
are
working
on
this
right
now,
but
one
thing
I
can
do
is
all
right.
A
I
want
to
get
my
inbox
and
my
team's
call
records
click
next
on
this
directly
from
here.
I
can
go
in
and
say
all
right,
so
for
my
inbox,
I
want
to
go
in
and
bring
the
data
for
my
legal
team
right,
so
really
wysiwyg.
What
you
see
is
what
you
get
kind
of
a
pro
trade.
Everything
is
very
visual.
Instead
of
you
having
to
create
your
pipeline
from
scratch,
I
want
to
get
all
the
emails
from
the
past
month
right.
I
could
do
the
same
thing.
A
Select
all
right
so
for
team
scholar
record
I'm
going
to
do
something
different,
I'm
going
to
go
in
and
this
I'm
going
to
select,
let's
say
the
the
finance
team,
all
right
so
really
sky's
the
limit
here.
You
can
go
click
next
on
this.
Yes,
I
need
to
specify
a
filter
in
here.
Apologies
for
this
and
then
we'll
have
a
second
morning
nick
as
well.
Our
next
presenter.
B
A
Good,
I'm
done
so.
Essentially,
then
what
will
happen?
Is
it
will
ask
you?
Where
do
you
want
to
go
and
store
it?
Click
next
it'll
create
a
pipeline
and
it'll
automatically
trigger
it
for
you
and
start
the
the
export
process.
So
what
I'll
do
is?
I
saw
a
couple
of
questions
in
chat,
I'll
answer
them
in
the
chat,
but
I
appreciate
you
folks
having
me
and
we're
moving
on
to
the
next
speaker
thanks
brian.