STAGE
|
BASIC
|
AVERAGE
|
IDEAL
|
1) Data Sources
|
Knowledge in the
heads of individuals.
|
Top 20 Applications known
with list of Data Sources and Owners
|
Agile
development with refactoring techniques.
|
|
No Data
Models and poor documentation of links between code and databases.
|
Basic Data
Dictionary in place.
|
Data Models and sign-off by
DBA on all changes.
|
|
|
|
User access and sign-off for
Data Dictionary
|
2) Data Integration
|
Ad-hoc integration using
bespoke SQL Scripts
|
Some Templates established
and commercial Tools in use.
|
MDM approved, data owner
sign-off,
Data Quality is an Enterprise issue.
|
|
|
Software Tools linked to the
Data Dictionary
|
Clear and
reconciled top-down and bottom-up views of data.
|
|
|
|
Data
Architecture and Data Models for Sources and Targets.
|
|
Nobody understands Master
Data Management (MDM)
|
MDM is planned
|
MDM is in place
|
2) Data Quality -
|
|
|
|
DQ level -
|
Could be improved
|
Sufficient
|
Accurate, valid and relevant
|
Policy -
|
Under consideration
|
Under implementation
|
Established as Enterprise Issue
|
|
|
|
|
3) Performance
Rpts
|
One-off, often independent
Dept. Spreadsheets
|
Independent Maps, KPIs and drill-down to detailed Reports
|
Integrated Maps, KPIs and drill-downs for Chief Exec
|
4) Internet Mashups
|
None
|
Isolated development
|
Users aware
|
5) Data Governance
|
None
|
No
end-to-end agreement.
|
Procedures published, Roles
and Responsibilities and Sign-off all in place.
|
|
|
|
Data
lineage known and auditable.
|