DATA GOVERNANCE FRAMEWORK Feedback on implementation at La Mutuelle Generale
Pascal Rabier
Chief Enterprise Architect
Jerome Capirossi
Enterprise Architect Consultant
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NATEA and LMG
Landmarks on Data quality
Framework principles
Framework main artefacts
DATA QUALITY GOVERNANCE FRAMEWORK
AGENDA
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Center of excellence for EntreprISe ARchitecture
TOGAF
NATEA IN ONE SLIDE
FEW WORDS ON NATEA
L’ENSEIGNE
Solutions
Standards Customers
Offering
Experience
Competences
Know-How
Strong partnerships
Contributions to
best practices
des grandes
entreprises
consultancy
Solutions
Training
Sessions
Coaching
E-learning
APM
BPM and
Architecture Framework
Approaches
Projects
Team
BPM
Enterprise
Architecture BAM
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LA MUTUELLE GÉNÉRALE (LMG)
FEW WORDS ON LA MUTUELLE GÉNÉRALE (LMG)
3rd French mutual - 12th health insurer
996,362 members
Protected persons: 1.4 million
One of the 1st operator in dependancy
(nearly 450,000 insured)
Gross earned premiums: € 1 021 million
Net income: € 24.5 million
Technical reserves: 1351 million €
(Life: 467 million € - Non-life: 884 million €)
Equity: € 576 million
Coverage ratio of solvency margin: 318%
risks (health and welfare)
Benefits under the Social Security System
Required:
1018 € million
CONCERNS
Operational concerns
• Competition requires to better assess
efficiency and to design effective action
plans
Regulatory concerns
• New Solvency II framework
• IFRS IV Framework
DATA QUALITY IS A CRITICAL SUCCESS
FACTOR
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Landmarks on Data quality
DATA QUALITY GOVERNANCE FRAMEWORK
AGENDA
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FRAMEWORK OF DATA CLASSIFICATION
CLASSIFY DATA ACCORDING LIFCYCYLE
LANDMARKS ON DATA QUALITY
Accounting, costs, budgets
Nomenclatures,
Codification
Valuation Hierarchies,
Dimensions
Tangibles, geography,
organization, persons
Products, Services,
Offers, Contracts,
Customers, Suppliers,
Partners,
contractualization
Employees, competence,
Job, training, career
Production, activities,
orders, Assignments,
Ressources
Monitoring, activities
changes
lifecycle
Refe
rence
Transa
cti
on
Décis
ion
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MODELING DATA DYNAMIC
LANDMARKS ON DATA QUALITY
Master
Data
PRE-TRANSACTION
Opérations
Domain
Control
Domain
BI
Domain
TRANSACTION VALUATION POST TRANSACTION
Context 1
Context …
Context n
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DATA GOVERNANCE IS A CROSS PROCESS
LANDMARKS ON DATA QUALITY
WHEN RISKS INDICATORS
PRE-TRAITEMENT
VALUATION
POST-TRANSACTION
POST-TRANSACTION
POST-TRANSACTION
External data not up to
date, Internal data
incomplete
Valuation Errors
Valuation Errors,
inconsistancies
inconsistancies
Loss of audit trail
Loss of archive
Actual
Understandable
Exact
Appropriate,
Accessible
Consistent,
Understandable
Actual,
Exact
Appropriate,
Consistent
PREPARE
PERFORM
MEASURE
DECIDE
AUDIT
ARCHIVE POST-TRANSACTION
Purge errors Consistent,
Accessible PURGE POST-TRANSACTION
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Codification
All coding and taxonomy rules changes should be prepared before launching transactions. No post
codification.
Consolidations are Intelligible and business meaning is clear
Transactions apply the entire coding
Data
The life cycle of data, their scope, context, their uses, their requirements and rules management, business
owners and their responsibilities are documented
The data are assign to an Architecture domain
Systems providing data processing services are identified and mapped.
Risks and safety measures associated with the data are identified, documented and validated
Data are accessible to entire company
Quality
Dashboards, data quality present regularly various indicators of data quality: quality control, quality assurance
Incidents affecting data quality are recorded as contingency measures
DEFINE A DATA QUALITY POLICY
LANDMARKS ON DATA QUALITY
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DEFINE ORGANIZATION AND PROCESS
LANDMARKS ON DATA QUALITY
Global data
Division Division Division
Sponsor
Sponsor Sponsor Sponsor
Business
Business Business
Business IT
IT IT
IT
context data
Business IT
context data
Business IT
context data
Business IT
context data
Business IT
context data
Business IT
Planning and
resource management
Financial
management
Demand
management
Contract
Management
Operational
supplier
management
Business data
management
End user
support
Use management cluster Functionality management cluster
Specify
information
requirements
Design
non-automated
Information
systems
Prepare
transition
Review and
testing
Change
manage-
ment
Transition
managem
ent
Management
processes
Operational
processes
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Framework principles
DATA QUALITY GOVERNANCE FRAMEWORK
AGENDA
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DATA GOVERNANCE ADDRESS BUSINESS OBJECTS, DATA ARE PROCESSED IN ACCORDANCE
A TOP DOWN REQUIREMENT FRAMEWORK
FRAMEWORK PRINCIPLES
Contrats
Produits
Assurés
Cotisations
Garanties
Quality Risks Business Objects
Exact Audit
Consistent Freshness
Conform Complete
Of Integrity Understanda
ble
Available
Data quality factors
REQUIREMENTSS CONTROLS
Data Data Data
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Framework main artefacts
DATA QUALITY GOVERNANCE FRAMEWORK
AGENDA
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FRAMEWORK METAMODEL
FRAMEWORK MAIN ARTEFACTS
Enterprise Data Entity
Organisation
Actor
Process
Business service
Data entity
Role
Function
Application components
Technologycomponents
platformcomponents
Business Service block
Business Service Quarter
Business Service Area
1
1
Up
da
te
Application
Togaf 9.1 Metamodel
concept
GroupingConcept
Enterprise Data QualityRequirement
Data Qualityrequirement
MetamodelExtension
Control
Enterprise Data QualityControl
Data QualityControl
Data RiskData quality aspects Enterprise Data event
Event
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BUILDING BLOCKS
LOGICAL ARCHITECURE
FRAMEWORK MAIN ARTEFACTS
Dataflow
Interface
Log of
controls
execution
Dataflow
Interface
Log of
controls
execution
Dataflow :
Entreprise Data entity event + Entreprise Data entity
token src token dst
Business
service
Business
service
Application Application
Data quality
manageme
nt
Requirements
and controls
master data
Identifier :
Dataset\ process\activity\control
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BUSINESS OBJECTS DICTIONARY
FRAMEWORK MAIN ARTEFACTS
Enterprise
Data Entity
- Definition
- Unique ID
- Type of Enterprise Data
- Owner
- Data Stewardship
- Master Application
- Data risks
- Quality requirements
- Archiving duration
- Business rules
- Linked enterprise data entities
- Enterprise Data Events
Data Entities - Definition
- Properties (name, description,
format)
- Data entity events
Enterprise
Data flow formats :
Enterprise Data Event, Data context,
Dataflow format
Glossaire
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DATA QUALITY INDICATOR
FRAMEWORK MAIN ARTEFACTS
00,5
11,5
22,5
33,5
44,5
5
Architecture framework and repository maturity
Data quality governance maturity
Architecture development maturity
Archi. performance measurement and
governance maturityData quality indicator
Quality of service indicator
Information system alignment indicator
Enterprise data quality indicator
Evaluation
Target
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FRAMEWORK MAIN ARTEFACTS
END
Q/A
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Jerome joined NATEA-Consulting in late 2010 to extend the Offer
Enterprise Architecture. In this context, he developed training
courses in Architecture and TOGAF 9.
He recently contributed to the working groups under the auspices
of CIGREF, of French ISACA and IFACI on good governance
practices of SI.
He is the author of a book on Enterprise Architecture released by
Editions Hermès-Lavoisier
Previously, he ran as a member of the Executive Committee, the
Cabinet Arismore consulting business specializing in Architecture
and representing OpenGroup in France for Enterprise
Architecture.
He worked for 10 years for a large integrator Logica on projects
due areas of the Bank and Energy
JEROME CAPIROSSI
ENTERPRISE ARCHITECURE
CONSULTANCY
ISACA Member
CESAMES meber
Certifications :
CISA
TOGAF 9 Certified
BISL Certified
Main customers : BNP CARDIF
GRT Gaz
AREVA – DSI Groupe –
Architecture d’Enterprise
EDF – Branche Commerce –
Architecture de programme
EIFFAGE – DSI – Stratégie des SI
SGCIB – Migration SWIFTNet – Architecture de
programme
LA POSTE – DSI – Stratégie des SI
MONOPRIX – DOSI – Architecture des SI
AUCHAN – Stratégie des SI
Author of : « Architecture d’Entreprise » chez
Hermès Lavoisier - Février 2011
: +33 6 34 43 70 53
Blogs : bizstrategos.com (in english)
capirossi.org (in french)