What is data governance? Best practices for managing data assets
BARC
recommends
the
following
steps
for
implementation:
Define
goals
and
understand
benefits
Analyze
current
state
and
delta
analysis
Derive
a
roadmap
Convince
stakeholders
and
budget
project
Develop
and
plan
the
data
governance
program
Implement
BARC
recommends
the
following
steps
for
implementation:
-
Define
goals
and
understand
benefits -
Analyze
current
state
and
delta
analysis -
Derive
a
roadmap -
Convince
stakeholders
and
budget
project -
Develop
and
plan
the
data
governance
program -
Implement
the
data
governance
program -
Monitor
and
control
Data
governance
vs.
data
management
Data
governance
is
just
one
part
of
the
overall
discipline
of
data
management,
though
an
important
one.
Whereas
data
governance
is
about
the
roles,
responsibilities,
and
processes
for
ensuring
accountability
for
and
ownership
of
data
assets,
DAMA
defines
data
management
as
“an
overarching
term
that
describes
the
processes
used
to
plan,
specify,
enable,
create,
acquire,
maintain,
use,
archive,
retrieve,
control,
and
purge
data.”
While
data
management
has
become
a
common
term
for
the
discipline,
it
is
sometimes
referred
to
as
data
resource
management
or
enterprise
information
management
(EIM).
Gartner
describes
EIM
as
“an
integrative
discipline
for
structuring,
describing,
and
governing
information
assets
across
organizational
and
technical
boundaries
to
improve
efficiency,
promote
transparency,
and
enable
business
insight.”
Importance
of
data
governance
Most
companies
already
have
some
form
of
governance
for
individual
applications,
business
units,
or
functions,
even
if
the
processes
and
responsibilities
are
informal.
As
a
practice,
it
is
about
establishing
systematic,
formal
control
over
these
processes
and
responsibilities.
Doing
so
can
help
companies
remain
responsive,
especially
as
they
grow
to
a
size
in
which
it
is
no
longer
efficient
for
individuals
to
perform
cross-functional
tasks.
Several
of
the
overall
benefits
of
data
management
can
only
be
realized
after
the
enterprise
has
established
systematic
data
governance.
Some
of
these
benefits
include:
-
Better,
more
comprehensive
decision
support
stemming
from
consistent,
uniform
data
across
the
organization -
Clear
rules
for
changing
processes
and
data
that
help
the
business
and
IT
become
more
agile
and
scalable -
Reduced
costs
in
other
areas
of
data
management
through
the
provision
of
central
control
mechanisms -
Increased
efficiency
through
the
ability
to
reuse
processes
and
data -
Improved
confidence
in
data
quality
and
documentation
of
data
processes -
Improved
compliance
with
data
regulations
Goals
of
data
governance
The
goal
is
to
establish
the
methods,
set
of
responsibilities,
and
processes
to
standardize,
integrate,
protect,
and
store
corporate
data.
According
to
BARC,
an
organization’s
key
goals
should
be
to:
-
Minimize
risks -
Establish
internal
rules
for
data
use -
Implement
compliance
requirements -
Improve
internal
and
external
communication -
Increase
the
value
of
data -
Facilitate
the
administration
of
the
above -
Reduce
costs -
Help
to
ensure
the
continued
existence
of
the
company
through
risk
management
and
optimization
BARC
notes
that
such
programs
always
span
the
strategic,
tactical,
and
operational
levels
in
enterprises,
and
they
must
be
treated
as
ongoing,
iterative
processes.
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