real-world data governance: master data management & data governance

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Copyright © 2012 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.comCopyright © 2012 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com

Non-Invasive Data GovernanceNon-Invasive Data Governance™ ™ is a trademark of Robert S. Seiner & KIK Consulting is a trademark of Robert S. Seiner & KIK Consulting

Twitter at #RWDGTwitter at #RWDG 1








Non-Invasive Data GovernanceNon-Invasive Data Governance™ ™ is a trademark of Robert S. Seiner & KIK Consulting is a trademark of Robert S. Seiner & KIK Consulting Twitter About This Webinar at #RWDGTwitter About This Webinar at #RWDG

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Robert S. SeinerRobert S. SeinerKIK Consulting & Educational Services – KIKconsulting.comKIK Consulting & Educational Services – KIKconsulting.com

The Data Administration Newsletter – TDAN.comThe Data Administration Newsletter – TDAN.com

Real-World Data GovernanceReal-World Data GovernanceMaster Data Management & Data GovernanceMaster Data Management & Data Governance

Making the Synergy Greater Than the PartsMaking the Synergy Greater Than the Parts

Monthly Webinar Series Hosted by DataversityMonthly Webinar Series Hosted by DataversityRobert S. Seiner – KIK Consulting / TDAN.comRobert S. Seiner – KIK Consulting / TDAN.com

August 16, 2012 – 2:00 p.m. ESTAugust 16, 2012 – 2:00 p.m. EST

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• Real-World Data Governance – Monthly Webinar SeriesReal-World Data Governance – Monthly Webinar Series– September 20, 2012 – September 20, 2012 – Business Glossaries & Data GovernanceBusiness Glossaries & Data Governance – 2pm EST – 2pm EST

– October 18, 2012 – October 18, 2012 – BI Governance and the Governance of BI DataBI Governance and the Governance of BI Data – 2pm EST – 2pm EST

– November 15, 2012 – November 15, 2012 – Tools of Data Governance – Tools of Data Governance – PurchasedPurchased and Developed and Developed – 2pm EST – 2pm EST

– December 20, 2012 – December 20, 2012 – Tools of Data Governance – Purchased and Tools of Data Governance – Purchased and Developed Developed – 2pm EST– 2pm EST

– Register On-Line at Dataversity.NetRegister On-Line at Dataversity.Net

Real-World Data GovernanceReal-World Data GovernanceUpcoming WebinarsUpcoming Webinars

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• Synergy is defined as the interaction of two or more agents or forces so Synergy is defined as the interaction of two or more agents or forces so that their that their combined impact is greater than the sum of their partscombined impact is greater than the sum of their parts..

• The word synergy perfectly describes the interaction between two of the The word synergy perfectly describes the interaction between two of the most talked about data management disciplines today, most talked about data management disciplines today, Master Data Master Data Management and Data GovernanceManagement and Data Governance..

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceAbstractAbstract

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• There are There are many tools on the market that enable organizationsmany tools on the market that enable organizations to address to address their MDM and DG concerns. their MDM and DG concerns.

• The challenge facing many organizations is to bring these two disciplines The challenge facing many organizations is to bring these two disciplines and the tools associated with these disciplines together in a and the tools associated with these disciplines together in a cohesive cohesive manner such that the sum of their partsmanner such that the sum of their parts exceeds the value that is added by exceeds the value that is added by each independent discipline.each independent discipline.

• Is there a Is there a practical way to do thispractical way to do this? Will the work effort required to achieve ? Will the work effort required to achieve MDM and DG success simultaneously make the practitioner’s life easier or MDM and DG success simultaneously make the practitioner’s life easier or more difficult?more difficult?

• The The answer lies in the approachanswer lies in the approach and andthe attention that is paid to addressthe attention that is paid to addressthese disciplines as a joint effort.these disciplines as a joint effort.


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• Join Bob Seiner and DATAVERSITY for the eighth in a series of monthly Join Bob Seiner and DATAVERSITY for the eighth in a series of monthly webinars titled “Real-World Data Governance” that will focus on levering webinars titled “Real-World Data Governance” that will focus on levering the the benefits of Master Data Management and Data Governance together benefits of Master Data Management and Data Governance together and and taking advantage of the relationship between the twotaking advantage of the relationship between the two to provide value to provide value beyond what can be expected from each discipline separately.beyond what can be expected from each discipline separately.

• Join us for another adventure in “Join us for another adventure in “Real-World Data GovernanceReal-World Data Governance”.”.


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• Governance – Governance – Execution of Enforcement and AuthorityExecution of Enforcement and Authority– Responsibility & AccountabilityResponsibility & Accountability

• Stewardship – Stewardship – Formalizing Accountability Formalizing Accountability – Formal – RecordedFormal – Recorded– Informal – Not Recorded – “People Just Know” – or do they?Informal – Not Recorded – “People Just Know” – or do they?

• Master Data – Master Data – Certifiable & Reliable DataCertifiable & Reliable Data– Master data objects are Master data objects are those core business objectsthose core business objects that are used in the that are used in the

different applications across the organizationdifferent applications across the organization, along with their , along with their associated associated metadata, attributes, definitions, roles, connections and metadata, attributes, definitions, roles, connections and taxonomiestaxonomies. .

David Loshin – Data Flux & MDM IntroDavid Loshin – Data Flux & MDM Intro

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceDefinitionsDefinitions

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• Master Data as a ProcessMaster Data as a Process– Process of Defining DataProcess of Defining Data– Process of Producing DataProcess of Producing Data– Process of Using DataProcess of Using Data

• Master Data as DataMaster Data as Data– Data by Master Subject Area Data by Master Subject Area – Data by Domain and Sub-DomainData by Domain and Sub-Domain– Data as System of Record or Single Point of TruthData as System of Record or Single Point of Truth

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceTwo Points of ViewTwo Points of View

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• Top Avoidable Governance & MDM Mistakes Top Avoidable Governance & MDM Mistakes (in no specific order) (in no specific order) : : – Lack of Executive & Strategic Level Understanding & SupportLack of Executive & Strategic Level Understanding & Support– Lack of Program Accountability & ResponsibilityLack of Program Accountability & Responsibility– Lack of Definition of Best Practices as a Target BehaviorLack of Definition of Best Practices as a Target Behavior– Lack of Critical Analysis of Present EnvironmentLack of Critical Analysis of Present Environment– Inability to Select & Follow Suitable ApproachInability to Select & Follow Suitable Approach– Lack of Planning and Ability to Support Meaningful InitiativeLack of Planning and Ability to Support Meaningful Initiativess– Framework of Roles & ResponsibilitiesFramework of Roles & Responsibilities– Making Data Governance & Data Quality OptionalMaking Data Governance & Data Quality Optional– Lack of Focus on CommunicationsLack of Focus on Communications– Improper Expectations of the Data Quality & Data Governance SolutionImproper Expectations of the Data Quality & Data Governance Solution– Failure to Stay Iterative and Incremental in the ApproachFailure to Stay Iterative and Incremental in the Approach

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceAvoidable MistakesAvoidable Mistakes

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• Master Data as a Master Data as a ProcessProcess::– Data Structure and Design (logical data model)Data Structure and Design (logical data model)– Data Storage (volume requirements)Data Storage (volume requirements)– Data Movement (extraction, transformation, load)Data Movement (extraction, transformation, load)– Data SecurityData Security– Data QualityData Quality– Data UsageData Usage– Data Function RequirementsData Function Requirements– Data System RequirementsData System Requirements

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceMaster Data as a ProcessMaster Data as a Process

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceMaster Data as a ProcessMaster Data as a Process

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• Master Data as Master Data as DataData::– Data Structure and Design (logical data model)Data Structure and Design (logical data model)– Data Storage (volume requirements)Data Storage (volume requirements)– Data Movement (extraction, transformation, load)Data Movement (extraction, transformation, load)– Data SecurityData Security– Data QualityData Quality– Data UsageData Usage– Data Function RequirementsData Function Requirements– Data System RequirementsData System Requirements

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceMaster Data as DataMaster Data as Data

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• Data Structure and Design (logical data model)Data Structure and Design (logical data model)– Governing the Design and the Structure of the Master DataGoverning the Design and the Structure of the Master Data– Governing the Meta-Data Associated with the Master Data (Definition, Rules, …)Governing the Meta-Data Associated with the Master Data (Definition, Rules, …)– Governing the Accessibility to the Meta-DataGoverning the Accessibility to the Meta-Data– Governing the Validation and Approval of the Structure and DesignGoverning the Validation and Approval of the Structure and Design

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceMaster Data as a Process / DataMaster Data as a Process / Data

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• Data Storage (volume requirements)Data Storage (volume requirements)– Governing the Storage of Master DataGoverning the Storage of Master Data– Governing the Volume Present and for Growth (Future Requirements)Governing the Volume Present and for Growth (Future Requirements)– Governing the Security of the Master Data ResourceGoverning the Security of the Master Data Resource– Governing the Retention and Life Cycle of the Master DataGoverning the Retention and Life Cycle of the Master Data– Governing the Backup and Recovery of the Master Data Governing the Backup and Recovery of the Master Data


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• Data Movement (extraction, transformation, load)Data Movement (extraction, transformation, load)– Governing the Movement of the Master DataGoverning the Movement of the Master Data– Governing the Selection of Data to be Master DataGoverning the Selection of Data to be Master Data– Governing the Transformation of DataGoverning the Transformation of Data– Governing the Loading of Data into the Master Data ResourceGoverning the Loading of Data into the Master Data Resource– Governing the Migration and Conversion of the DataGoverning the Migration and Conversion of the Data


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• Data SecurityData Security– Governing the Security of the Master DataGoverning the Security of the Master Data– Governing the Classification and Handling of the Master DataGoverning the Classification and Handling of the Master Data– Governing the Accessibility of the DataGoverning the Accessibility of the Data– Governing the Risk Associated with Master DataGoverning the Risk Associated with Master Data


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• Data QualityData Quality– Governing the Quality and Certification of Master DataGoverning the Quality and Certification of Master Data– Governing the Definition of Standards and ValuesGoverning the Definition of Standards and Values– Governing the Collection and Publication of StandardsGoverning the Collection and Publication of Standards– Governing the Process of Recording Data Quality IssuesGoverning the Process of Recording Data Quality Issues– Governing the Process of Resolving Data Quality IssuesGoverning the Process of Resolving Data Quality Issues


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• Data UsageData Usage– Governing the Use of Master DataGoverning the Use of Master Data– Governing the Definition and Production of the Master DataGoverning the Definition and Production of the Master Data– Governing Who Can Access and See the DataGoverning Who Can Access and See the Data– Governing the Understanding of the Master DataGoverning the Understanding of the Master Data– Governing the Production and Distribution of Reports and DataGoverning the Production and Distribution of Reports and Data– Governing the Audit and Compliance of the DataGoverning the Audit and Compliance of the Data


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• Data Function RequirementsData Function Requirements– Governing the Process of Defining Functional Requirements for Master DataGoverning the Process of Defining Functional Requirements for Master Data– Governing the Documentation of the RequirementsGoverning the Documentation of the Requirements– Governing the Approval of the RequirementsGoverning the Approval of the Requirements– Governing the Process of Meeting Functional RequirementsGoverning the Process of Meeting Functional Requirements


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• Data System RequirementsData System Requirements– Governing the Process of Defining System Requirements for Master DataGoverning the Process of Defining System Requirements for Master Data– Governing the Documentation of the RequirementsGoverning the Documentation of the Requirements– Governing the Approval of the RequirementsGoverning the Approval of the Requirements– Governing the Process of Meeting System RequirementsGoverning the Process of Meeting System Requirements– Governing Around the Design ConstraintsGoverning Around the Design Constraints– Governing to Performance RequirementsGoverning to Performance Requirements– Governing to Data Quality and Production Support RequirementsGoverning to Data Quality and Production Support Requirements– Governing to Usability RequirementsGoverning to Usability Requirements


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Operational LevelOperational Data Stewards (existing)

Data Definers, Producers, UsersThese people are presently defining,producing and using data as part of theirjobs. Recording of the Operational DataStewards will be an important enabler ofimproved communications, coordinationand cooperation among stewards.

Tactical LevelData Domain Stewards

Per assigned Subject AreasData Steward Coordinators

One per Business Unit

Strategic LevelData Governance CouncilData Governance Sponsors Groupor Group of similar participation. One person, plusalternate, for each Business Unit represented & IT.Consider financial services & human resources.

Executive LevelData Steering CommitteeSenior-most level knowledge of the program.Leverage existing business structure as possible.If no structure exists, utilize an IT Steering Committeeor an executive founded board or council.

Operational Level - Business Unit Specific

Strategic -Enterprise

Tactical Level - Cross Business Unit

Executive

“Non-Invasive Data Governance”™ Operating Modelof Roles & Responsibilities

Escalation / Approval Path

Copyright © 2009 - Robert S. Seiner - KIK Consulting & Educational Services, LLC - All Rights Reserved

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Data Governance Program TeamData Governance Team ManagerResponsible for Administering the Program,facilitating use of the Data Governance Council,communicating program components and value to the Organization.Advisory assistance from other levels.

IT Subject Resource ExpertsSystem/Data Resource ExpertsIT Staff including ApplicationDevelopment, Data Design,Security, and other DataResource Management.

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KIK Consulting & Educational Services, LLC

EXISTS

EXISTS

EXISTS

EXISTS

EXISTS

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceMaster Data Roles & ResponsibilitiesMaster Data Roles & Responsibilities

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceMaster Data Roles & ResponsibilitiesMaster Data Roles & Responsibilities

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceGoverning Master Data CommunicationsGoverning Master Data Communications

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceApplying Governance to Master DataApplying Governance to Master Data

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• Pro-Active Data GovernancePro-Active Data Governance– Build application of stewards into existing project management methodologyBuild application of stewards into existing project management methodology

• Reactive Data GovernanceReactive Data Governance– Build application of stewards into data quality methodologyBuild application of stewards into data quality methodology– Build application of stewards into issue resolution processBuild application of stewards into issue resolution process

• TriggersTriggers– Using Stewards & Recorded Steward Metadata to Demonstrate Communications Using Stewards & Recorded Steward Metadata to Demonstrate Communications

Improvement Improvement

• Escalation & ResolutionEscalation & Resolution– Using Stewards & Recorded Steward Metadata to Get … the Using Stewards & Recorded Steward Metadata to Get … the “Right” “Right” People Involved in People Involved in

the the “Right” “Right” Decisions at the Decisions at the “Right” “Right” Time.Time.

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DATA DEFINERDATA

PRODUCER

DATA STEWARDCOORDINATOR

MASTER DATA GOVERNANCE ACTIVITY MATRIX

MASTER DATA DEVELOPMENT

LIFE CYCLE(MDDLC)

INFORMATION GATHERING

(DOMAIN, SYSTEM, STEWARDS)

OPERATIONAL DATA STEWARDS

DATA USER

DATA DOMAINSTEWARD

(or designee)

DATA DOMAIN / LOB/FUNCTIONAL AREA

ASSESSMENT &REQUIREMENTS

PLANNING &ANALYSIS

SOLUTION DESIGN

SOLUTION DEVELOPMENT

SOLUTION TESTING

SOLUTION IMPLEMENTATION

SOLUTION MONITORING &MAINTENANCE

Activity initiated re: this domain,Data Domain Steward is involved in identifying and recording info related Domains, Systems, Stewards per issue or task.

Activity initiated re: this domain,Steward Coordinator is involved in identifying Operational Stewards in this LOB/FA that should participate in this work flow. Assure appropriate business meta-data is recorded.

Propose alternatives for data definition solution that best fits with defined requirements.

Provide input to the development of the data production solution.

Coordinate tasks associated conducting the assessment and requirements steps.

Provide definition requirements & gathering document. Define data needed to operate business & report results.

Test data solution from a definition perspective. Assure that appropriate business meta-data is recorded.

Provide production requirements per definition. Produce data needed to operate business & report results.

Produce user requirements. Use data needed to operate business & report results.

Coordinate activities of Operational Stewards including project timelines, status reporting, tactical decision making. Assure appropriate business meta-data is recorded.

Coordinate activities of Operational Stewards including project timelines, status reporting, tactical decision making.

Provide data definition guidance to build the appropriate solution.

Provide data production guidance to build the appropriate solution.

Provide data usage guidance to build the appropriate solution.

Coordinate tasks associated conducting planning and analysis steps.

Propose alternatives for data production that best fits with the data definition solution and defined requirements.

Propose alternatives for data usage solution that best fits with defined requirements.

Coordinate activities of Operational Stewards including timelines, reporting. Propose solution to Data Domain Steward. Assure appropriate business meta-data is recorded.

Coordinate tasks associated conducting planning and analysis steps. Accept or Resolve solution from the Steward Coordinator.

Coordinate activities of all individuals related to development work including timelines, status, tactical decision making.

SYSTEM SMEs

IT

DATA SMEs

Test data solution from a production perspective. Assure that appropriate business meta-data is recorded.

Test data solution from a usage perspective. Assure that appropriate business meta-data is recorded.

Coordinate activities of the Operational Stewards related to testing work including timelines, status, tactical decision making.

Coordinate activities of the Operational Stewards related to solution implementation including timelines, status, tactical decision making.

Coordinate activities of the Operational Stewards related to solution monitoring & maintenance including timelines, status, tactical decision making.

Perform EIS system testing. Assure that appropriate technical meta-data is recorded.

Perform EIS data testing. Assure that appropriate technical meta-data is recorded.

Coordinate and manage all technical aspects of data solution development. Assure that appropriate technical meta-data is recorded.

Coordinate and manage all technical aspects of system solution development. Assure that appropriate technical meta-data is recorded.

Coordinate system design with Data Domain Stewards and Steward Coordinators.

Coordinate data design with Data Domain Stewards and Steward Coordinators.

Coordinate and manage all technical aspects of system planning and analysis with Data Domain Stewards and Steward Coordinators.

Coordinate and manage all technical aspects of data planning and analysis with Data Domain Stewards and Steward Coordinators.

Coordinate and manage all technical aspects of system assessment & requirements gathering with Data Domain Stewards and Steward Coordinators.

Coordinate and manage all technical aspects of data assessment & requirements gathering with Data Domain Stewards and Steward Coordinators.

Coordinate and manage all technical aspects of data information gathering with Data Domain Stewards and Steward Coordinators. Assure appropriate technical meta-data is recorded.

Coordinate and manage all technical aspects of system information gathering with Data Domain Stewards and Steward Coordinators. Assure appropriate technical meta-data is recorded.

Participate in data definition information gathering as needed.

Participate in data production information gathering as needed.

Participate in data usage information gathering as needed.

Coordinate and manage all technical aspects of system solution implementation.

Coordinate and manage all technical aspects of system solution monitoring & maintenance.

Coordinate and manage all technical aspects of data solution implementation.

Coordinate and manage all technical aspects of data solution monitoring & maintenance.

Coordinate business tasks associated with solution testing steps.

Coordinate business tasks associated with solution implementation.

Coordinate business tasks associated with solution monitoring & maintenance.

As part of daily job, identify operation data issues pertaining to their domain of data.



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Legend: Gray Block w/Bold X = Active Participant, Block w/Dull X = Optional Participant, * See Appendix for Template

Outcome / DeliverablesProcess Step

X

X

X

X

X

X

X

X

X

X

X

X

X

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X

X

X

X

X

X

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Meta-D

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Meta-D

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Meta-D

ata Defin

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Meta-D

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Meta-D

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Meta-Data StewardsMapped to Meta-Data

Processes

Conceptual Modelof Taxonomy

Data Analysis for Data Listed inStep 3

Mapping of Source Data toData

Change Control, Versioning &Security Requirements

Documentation Validating“Best” Source

Data Movement, User Interface& Functional Development

Data List PerBusiness Requirements

Attributed Logical Model ofTaxonomy

XX X X X X Sign Off of Data Validationin the Repository

X

X X

X

1. Develop Conceptual Model /Data Taxonomy

4. Conduct Data Analysis of Attributes UsingData Analysis Template

5. Map Sources of Source Data toRepository Data Structures

6. Assess Change Control, Versioning, Security

7. Selection of the “Best” Sourcefor the Data

8. Design and Develop theData “Engine” and User Interface

2. Further Develop Logical ModelIncluding Attribution of Entities

9. Validate and Test Data

3. Specify Which Taxonomy Attributes Will BeIncluded in the Repository

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceResolving Master Data Management IssuesResolving Master Data Management Issues

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Master Data Management & Data GovernanceMaster Data Management & Data GovernanceApplying Governance to Master Data Meta-DataApplying Governance to Master Data Meta-Data

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• Master Data as a ProcessMaster Data as a Process– Process of Defining DataProcess of Defining Data– Process of Producing DataProcess of Producing Data– Process of Using DataProcess of Using Data

• Master Data as DataMaster Data as Data– Data by Master Subject Area Data by Master Subject Area – Data by Domain and Sub-DomainData by Domain and Sub-Domain– Data as System of Record or Single Point of TruthData as System of Record or Single Point of Truth

Master Data Management & Data GovernanceMaster Data Management & Data GovernanceSummarySummary

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• Robert S. SeinerRobert S. SeinerKIK Consulting & Educational Services – KIKconsulting.comKIK Consulting & Educational Services – KIKconsulting.comThe Data Administration Newsletter – TDAN.comThe Data Administration Newsletter – TDAN.comPost Office Box 112571, Upper St. Clair, Pennsylvania 15241Post Office Box 112571, Upper St. Clair, Pennsylvania 15241412.220.9643, 412.220.9644 (Fax)412.220.9643, 412.220.9644 (Fax)[email protected]@[email protected]@tdan.com

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