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Cre
ativ
e C
om
mo
ns
Sustainable IT Architecture
MDM and Semantic modeling
2010, May
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Sustainable IT Architecture
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Enterprise Data GovernanceReference and Master Data Management
Semantic Modeling
By Pierre Bonnet - 2010, MayCreative Commons
www.sustainableitarchitecture.com
To order the book:http://www.orchestranetworks.com/book-enterprise-data-governance.html
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What we deliver
Open community working on MDM+BRMSand the IS Rating Tool
Open Communityworking on
Semantic Data modeling and EA applied to MDM
²
Software Vendor in Model Driven MDM and
Data Governance
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MDM… Why?
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Where are your ref/master data?
A product (Database No. 1) is only created if the factory code (Database No. 2) which it is affiliated with is under the management of an organization
(Database No. 3) that has an ongoing production agreement (Database No. 4) with the company or one of its partners (Database No. 5), that has been active
for the past twelve months, at its disposal
Product Factory Organization
Agreement Partner
Database No.1 Database No.2 Database No.3
Database No.4 Database No.5
?
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Solution:MDM and Data Governance approach
Product
Database No.1
Factory
Database No.2
Organization
Database No.3
Agreement
Database No.4
Partner
Database No.5
MDM
Package
Produit Usine
Organisation
Accord de production
fabrique
* *
gère*
1
rôle 1
rôle 2
*
A product (Database No. 1) is only created if the factory code (Database No. 2) which it is
affiliated with is under the management of an organization (Database No. 3) that has an
ongoing production agreement (Database No. 4) with the company or one of its partners
(Database No. 5), that has been active for the past twelve months, at its disposal
Mas
ter
Dat
a In
teg
rati
on
(E
AI/E
SB
/ET
L)
Rich and shared master data model
Product Factory
Organization
Agreement
affiliated
managed
role 2
role 1
Data Steward
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Three axis for every data element
priceprice
priceprice
priceprice
priceprice
priceprice
priceprice
priceprice
priceprice
Version
Time
Use context
The price master data value depends on- a version (e.g. business regulation),- a period of time (e.g. a quarter)- and a use context (e.g. a sales channel)
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Data Governance: version management
Version management: compare and merge your data versions
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Data Governance: contexts management
Contexts management: data authoring by uses contexts
Permissions delegation
Inheritance ofvalues
Corporate
Partner 1 Partner 2
Threshold = [10, 100]
Threshold = [20, 90]Threshold = inherited
Agency Web
Threshold = [25, 50]
Partner
Call-centerWeb
Corporate
Sales Channels
= use context
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Data Governance: other key features
• Ability to customize default UI• Permissions management• Data history management• Data hierarchy management• Data approval workflow• Data archiving• Data query and reporting• Data web services• ../..
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Which data quality is the right one?
Level 1 – BASIC DATA QUALITY
• Sticking cleansing toolson existing silos and databases
• Lack of data governance
Level 2 – EXTENDED DATA QUALITY
MDM
• Data repository with limited data governance functions as it doesn’t rely on a semantic data model. Its data model has a similar structure to existing databases schemas
Level 3 – TOTAL DATA QUALITY
MDM
• Data repository based on a rich data model independent of existing databases schemas. It brings all data governance functions aligned with the semantic data modeling
Data Steward
Low
Medium
Optimized
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Model-driven lives with OLTP systems
Model-driven MDM
Rich data model over OLTP RDBMS
Business objects, lifecycles, validation rules, permissions G
ov
ern
anc
e ti
me
CDI (OLTP system)
Rigid data model in OLTP RDBMS
Data Injection
To data governanceR
un
time
Consolidation and data enrichment
Transactional IT System
RDBMS TablesRDBMS Tables
Data Steward
Usual users of the IT system
All data governance functions are automatically driven by the rich data model
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Towards what IS transformation?
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IS transformation path: stage 1
R/M
Functional silo
R/M
Functional silo
R/M
Functional silo
MDM
Ref/Master data
Unified data model
Step 1. MDM is synchronized with existing
databases
Data governance
Referential/Master data
R/M
Transactionaldata
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IS transformation path: stage 2
R/M
Functional silo
R/M
Functional silo
R/M
Functional silo
MDM
Ref/Master data
Unified data model BRMS
Business Rules
Step 2. BRMS is used for extracting business
rules locked in silos
Data and Rules governance
Referential/Master data
R/M
Transactionaldata
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IS transformation path: stage 3
New system
Functional silo
R/M
Functional silo
MDM BRMS BPM
Business Rules ProcessesMaster Data
R/M
IS governance (Data, Rules, Processes)
Referential/Master data
R/M
Transactionaldata
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Linking value: MDM+BRMS+BPM
source: SMABTP insurance company
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MDM… Which modeling procedures?
Caveats: this presentation doesn’t tackle organization issues when deploying and managing a MDM. To get information about this governance topic, please read the book (chapter 7) and/or visit our website www.sustainableitarchitecture.com
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Which MDM is the right one?
Virtual MDM
Static MDM
DANGER
Semantic MDM
Richness and expressiveness
Level of modeling
Semantic data modeling
Classic data modeling
IT BusinessAmbiguous
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Semantic MDM gains: example 1
Use context Cardinality (n) Cardinality (p)
Head Office 0 1
Subsidiary 1 5
Partner 1 1
../..
MDM
Produit Usine
* on use context (n,p)Product Factory
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Semantic MDM gains: example 2
Semantic modeling
Author Book* *
writes
This (very simple) semantic data model must be translated into a logical data model runnable by the MDM software
• either via join table (static MDM)• or via an object-oriented approach relying on a MDA architecture
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Join Table(IT point of view)
Auteur
PKAuteur : real
Livre
PKLivre : real
AuteurLivre
FKAuteur : real
FKLivre : real
PKLivre : realPKAuteur : real
FKAuteur : real
FKLivre : real
Logical data model with join table
AuthorBook
FKAuthor : real FKBook : real
Author Book
PKAuthor : real PKBook : real
Logical data model without join table (semantic is maintained)
Auteur
PKAuteur : real
Livre
PKLivre : real
lstFKAuteur [*] : real
PKAuteur : real PKLivre : real
lstFKAuteur [*] : real
*
Model-driven: the screen is automatically generated from the rich data model
Author Book
PKAuthor : real PKBook : reallstFKAuthor[*] : real
Semantic MDM
Static MDM
=> entails hard-coding to hide join tables
=> what you model is what you get
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Method: mustn’t be dedicated to the MDM
Regardless of any specific method, at the very least these key points must be enforced to succeed in MDM projects:
• Semantic modeling• Enterprise Data Architecture• Logical data modeling… and that’s all
LogiqueLogicalS?mantiqueSemantic
PragmatiquePragmatic
G?ographiqueGeographic Mat?rielHardware
TechniqueTechnical
LogicielSoftware
PhysiquePhysicalPraxeme example – figure from Praxeme Institute (creative commons)
see detailed information in the book
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Enterprise Data Architecture
Domain of business objects
Domain of business objects
Domain of administrative objects
Domain of administrative objects
Category
Category
Category
Category
Business Object
Business Object
Business Object
Category
Category
Business Object
Business Object
Business Object
Business Object
Data form
Foreign Key
Data form
Administrative Object
Administrative Object
Administrative Object
Domain of business objects
Domain of business objects
Domain of business objects
Domain of business objects
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Data Category
Data category Client Data category Order
Client
Commande
Classement
<<comment>>
Liaison par clefs étrangères (FK)
Préférence
<<comment>>
Liaison par une liste de types imbriqués
<<comment>>
Liaison par un type imbriqué
PKClient : real
FKCommande [*] : real
Classement : Classement
Préférence [*] : Préférence
Tig
htl
y co
up
led
Lo
ose
ly c
ou
ple
d
Classification
PKClient : realFKOrder[*] : realClassification : ClassificationPreference[*] : Preference
Preference
Client
Order
<<comment>>
Linked with nesteddata type
<<comment>>
Linked with a list ofnested data types
<<comment>>
Linked withforeign keys (FK)
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Enterprise Data Architecture
Career plan
Person
Career plan
Person
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Let's take a quick exampleBusiness object: Address
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This is not a semantic data model
• lack of referential integrity constraints
• no business lifecycle, i.e. no state attribute whereas this is an important ref/master data attribute
• very poor expressivity as this data model is a flat point of view (data flows)
If this data model is used to manage Address within the MDM… this is the end of MDM
Figure stemming from OASIS
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Address
Object
SiteCoordinate System Code
Location coordinate
::MAG::Business::Utilities::Period
0..1
language
location nature
longitude minutes measure : real
latitude degrees measure : real
latitude minutes measure : real
latitude direction code : real
longitude degrees measure : real
longitude direction code : string
identification code : string
description : string
* *locates
* resides
1
short name : string
full name : string
other details : Text
*
building number (address line 1) : integer
number for the nature (address line 2) : integer
name for the nature (address line 2) : string
additional name (address line 3) : string
post box : string
floor : string
room : string
other details [*] : Text
building name (address line 1) : string
Semantic modeling –
Address stage 1
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Address
Object
Country
Currency Code
SiteCoordinate System Code
Location coordinate
City
Territory
Territory Type
Territory Office
Address Nature
Address Code
Postal Code Pattern
Type Territory Office
::MAG::Business::Utilities::Period
*order
manages0..1
language
location nature
1
longitude minutes measure : real
latitude degrees measure : real
latitude minutes measure : real
latitude direction code : real
longitude degrees measure : real
longitude direction code : string
identification code : string
description : string
* *locates
* resides
*
serves
name : string
code : string
special code : string
1
0..1 *
1..*
divides in
nom : string* 1
defines
short name : string
full name : string
other details : Text
*
building number (address line 1) : integer
number for the nature (address line 2) : integer
name for the nature (address line 2) : string
additional name (address line 3) : string
archive()
locates
name : string
name : string
name : string0..1
1
post box : string
floor : string
room : string
other details [*] : Text
building name (address line 1) : string
check()
start()
*
locates
*
description : string
pattern : string
remove()
complete()
1
territory name : stringincludes
regional phone prefix : string
international phone prefix : string
territory code used : boolean
mail office
manages
city name : string
city code : string
/postal code : string
1
* *
locates
0..1
0..1
/relates to
*
1
*
*
/locates
manages through
time zone offset : string
territory code : string
1
*locates
name : string
time zone offset : string
uses
1 *
* 1
structures by
*
defines
0..1
1
1
Semantic modeling –
Address stage 2
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Return To Sender (RTS)
To be checked Valid
To be completed
Archive
Undeliverable as Addressed
Insufficient Address
No such numberstart/start()
check/check() [ok]
[undeliverable]
[insufficient]
[no such number]
[not complete]
complete/complete()
archive/archive()
archive/archive()
remove/remove()check/check()
Semantic modeling –
Address stage 3Business lifecycle (state machine)
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Decision table applied to Address
BUSINESS STATES
ADDRESS Valid Archive
building number yes no yes no no no no no
number for the nature yes no yes no no no no no
name for the nature yes no yes no no no no no
additional name yes no yes no no no no no
building name yes no yes no no no no no
post box yes no yes no no no no no
floor yes no yes no no no no no
room yes no yes no no no no no
other details[*] yes yes yes yes yes yes yes no
yes = modif ication possible / no = modif ication impossible
To be checked
To be completed
Return to Sender (RTS)
Undeliv erable as Addressed
Insuf f icient Address
No such number
Carried out by the MDM automatically when checking data modifications of Address. It means less approach of hard-coding software and more auditability and traceability of integrity constraints applied to ref/master data
MDM
Stored into the MDM
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Which project management?
It depends on the maturity level of the MDM tool
• either a nightmare with significant risks of MDM collapse• or easier way relying on Model-driven approach
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Decision of the integration mode:weak, tight or loose coupling
Semantic modeling andOrganization modeling
Decision of the MDM architecture style:Classic OLTP versus Model-driven
Relational oriented logical data model
Hard-coded and bespoke software development for
validation rules and to align data governance functions
Rich logical data model including
business objects’ lifecycles and data
validation rules
MDM
ref/master data
MDM (model-driven)
ref/master data
MDM locked in hard-coded software. It
becomes a new silo
MDM open for business users with full data
governance functions
Model-driven MDMClassic OLTP
MDM project
“What you model iswhat you get”
Weak coupling MDM (§12.1.1.)
Tight coupling MDM (§12.1.2.)
Loose coupling MDM (§12.1.3.)
tunnel effect iterative delivery
see the book
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How to drive and measure theIS transformation based on MDM?
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How to assess the IS Value?
• Use Value• Deals with an assessment of company’s
working procedures used by IS stakeholders to communicate, build, maintain and run their Information Systems
• Business Value • Regardless of working procedures,
it measures the ability to align the IS with business strategy and operational requirements. It also includes financial measurement
• Intrinsic Value• It is the actual value of IS Assets
regardless of its Use Value and its Business Value, based on ref/master data, business rules and processes
ISO900x, CobiT, CMMI, PRINCE2, ITIL,TOGAF, etc.
CobiT, ITIL, IAS-IFRS, etc.
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Each IS Asset is gauged through a set of questions grouped by three facets Knowledge, Governance Features, IT Approach
IS Rating Tool matrix
Note: The governance features facet is focus on a list of functions required to well manage Data, Rules and Processes such as Version management, Authoring, Traceability, etc. This is not the quality of processes applied to conduct changes and relationships between Executives, Business Users and IT department.
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Each cell of the IS Rating matrix is defined through a list of questionsto measure the IS Assets
IS Rating Tool matrix
Five marks levels are available for each question
Bad: 0% to 15%
Basic: 15% to 30%
Medium: 30% to 50% Advanced: 50% to 80% Optimized: 80% to 100%
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A consolidated rating is obtained in the form of three letters Each letter gives a consolidated Performance Level Percentage
(PLP) regarding your Data, Rules and Processes respectively
A: >=90% B: >=50% and <90% C: >=10% and <50% D: <10%
Letter #1 Letter #2 Letter #3
IS Rating approach
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IS Rating example – 1/4
This company has a huge risk in Data management (C) and Rules management (C). Its ability to well manage its Processes (B) doesn’t prevent this company from facing a serious IS crisis because of a data and/or business rules loss of control. More precisely, according to its detailed IS rating outcomes, we have to study why its data knowledge is so poor (only 5% = D)? From this first rating, the company’s stakeholders should demand detailed information describing the IS plan to manage data and rules risks.
Once this plan will be delivered, a further IS rating will be done to gauge the IS improvement. May be, this company could decide to raise its data consolidated mark to the "B" level within a year and then attain a "BCB" rating which would be reassuring for its stakeholders.
Then, after a full year of work on data knowledge improvement, the company’s rating goes up to "BCB” (see the next rating card).
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IS Rating example – 2/4
On the basis of this new rating, the company has a huge interest in improving its business rules management to reach a ‘B’ level rather than a poor ‘C’. The key factor to succeed seems to deploy a stronger approach in rules governance, as shown in its detailed IS rating outcomes (21% = C).
After delivering works on rules management, this company achieves this objective and attains a new rating "BBB" (see the next rating card).
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IS Rating example – 3/4
"BBB" is an excellent rating, very reassuring for all IS stakeholders. By analyzing its detailed percentage levels per IS assets (see its detailed IS rating outcomes) additional improvements can be identified to target the "AAA" level.
Don't forget, the rating can be established both at the scale of the whole IS but also within a smaller scope such as a subsystem, a software package, a subsidiary, a web application, etc.
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IS Rating example – 4/4
A progressive path to leverage yourIS Intrinsic Value and drive your Enterprise Architecture
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IS Rating Tool - Excerpts
On the web site www.sustainableitarchitecture.com
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g Facets of the rating: Data, Rules, Processes. Here is the Data Assessment spreadsheet
Questions to measure IS AssetsHow to answer
Guidelines
The marks from Bad to Optimized
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IS Rating Dashboard
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S-IT-A in the EA and ERP fields
• Lot of EA approaches but lack of a common foundation to transform IS and measure outcomes
ACMS brings the foundation IS Rating Tool measures
outcomes instead of processes
• ERP benefit from the ACMS foundation Assess your ERP through the IS
Rating Tool
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• Audit tool used within IT departments to encourage innovation and to
assess Enterprise Architectures
• Audit tool to assess IS scopes such as departments, business
units, systems, applications, etc.
• Communication tool between IT department and all IS Stakeholders
• Tool for getting key indicators required to establish an annual IS
Assessment published to company's Stakeholders
• Tool used to encourage bench-learning between companies
• Audit tool when selecting software packages such as ERP, CRM, Supply
Chain, etc.
• Audit tool to complement with financial analysis when studying and
driving M&A (Mergers and Acquisitions)
• Tool to support IS innovation based on the ACMS foundation, in other
words business repositories relying on MDM, BRMS and BPM
• Tool to drive third parties IS/IT contracts by including it within RFQ and
RFP as a set of commitments
When using the IS Rating Tool?
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CobiT mapping with ACMS & IS Rating
FOUNDATION MEASURE / CONDUCT
CobiT - PO1 Define a Strategic IT PlanPO1.1 IT Value Management PO1.2 Business IT AlignmentPO1.3 Assessment of Current Capability and PerformancePO1.4 IT Strategic Plan
CobiT - PO2 Define the Information Architecture PO2.1 Enterprise Information Architecture ModelPO2.2 Enterprise Data Dictionary and Data Syntax RulesPO2.3 Data Classification Scheme
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Excerpt: PO1.1 IT Value Management
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Excerpt: PO2.1 IT Enterprise Information
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How to contribute toSustainable IT Architecture
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Year plan 2010 focus on IS Rating Tool
End of June 2010
• First official version of the IS Rating Tool
September 2010
• Beta one-day training IS Rating Tool
October/November 2010
• Annual conference S-IT-A dedicated to the IS Rating Tool
End of 2010
• Official one-day training and certification IS Rating Tool
• First implementation within EA Tools
• New book “IS Assets and EA”
• New version with a derivation to business users
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Year plan 2010 – To contribute
Working group IS Rating Tool
• To improve, to test, to provide feed-backs and bench-learning
EA Tools
• We need to partner with software vendors in EA field
Annual conference on October/November 2010
• We are willing to welcome sponsors
Lobbying and exchanges
• Linkedin Group (more than 900 members)
• Added-values by System Integrators over the core IS Rating Tool
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How to participate in Sustainable IT?
To accelerate the adoption of ACMS and
IS Rating Tool we need your support Systems Integrators can benefit from
the S-IT-A web platform to give
information about their added-values
based on ACMS and IS Rating Tool
User Companies can show their
interests in ACMS and IS Rating Tool,
publish and share lessons learnt and
therefore contribute to the effort of the
community
Individual contributors and testers of the
IS Rating Tool are welcome
(more than 100 members)
To stay tuned everyone is welcome to our
linkedin group
(more than 900 members)
complete list on our website
complete list on our website
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www.sustainableitarchitecture.com
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To contact Pierre Bonnet, Founder of Sustainable IT Architecture Communitypierre.bonnet@orchestranetworks.com
To order the book:http://www.orchestranetworks.com/book-enterprise-data-governance.html
Book by Pierre Bonnet. ISBN: 9781848211827Publication Date: May 2010ISTE - Wiley
Table of contents
The MDM Approach1. The Company and its Data.2. Strategic Aspects.3. Taking into account ERP.4. Return on Investment.
MDM for Business Users5. MDM Maturity Model.6. Data Governance Features.7. Organizational Aspects.
The MDM for IT Specialists8. Key Principles of Semantic Modeling.9. Semantic Modeling Procedures.10. Logical Data Modeling Procedures.11. Organization Modeling Procedures.12. MDM-IT integration
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