Master Data ManagementMaster Data ManagementBlending what Business Needs with what I.T. Blending what Business Needs with what I.T.

NeedsNeeds

presented by Dawn Michelspresented by Dawn MichelsInformation Architect of Andersen Corp.Information Architect of Andersen Corp.

Feb 21, 2007Feb 21, 2007

AgendaAgenda

Defining Master Data Defining Master Data ManagementManagement

Three Aspects of MDMThree Aspects of MDM– Knowledge (Business Context)Knowledge (Business Context)– Content Content – MaintenanceMaintenance

Business Needs vs. I.T. ExpectationsBusiness Needs vs. I.T. Expectations

MMD

– – Master Data Mgmt Master Data Mgmt is…is…

Master Data Management is the business Master Data Management is the business processes combined with the technical processes combined with the technical infrastructure required to provide and infrastructure required to provide and maintain consistent and accurate sets of maintain consistent and accurate sets of master datamaster data

It includes but is not limited to:It includes but is not limited to:– MetadataMetadata– ToolsTools– Business and Technical ProcessesBusiness and Technical Processes– Integration of data from disparate systemsIntegration of data from disparate systems

MMD

A couple of A couple of approachesapproaches

Subject AreaHub

Source 1

Source 2

Source 3

Source 4

Source 5

Source 6

Shareable data

AgendaAgenda

Defining Master Data ManagementDefining Master Data Management Three Aspects of MDMThree Aspects of MDM

– Knowledge (Business Context)Knowledge (Business Context)– Content Content – MaintenanceMaintenance

Business Needs vs. I.T. Business Needs vs. I.T. ExpectationsExpectations

MMD

Master Data Master Data KnowledgeKnowledge IdentificationIdentification Corporate Business ValueCorporate Business Value ROIROI Data Governance & StewardshipData Governance & Stewardship

Identifying Key Identifying Key SubjectsSubjects Identify where the business needs meet the Identify where the business needs meet the

willingness to accumulate, manage and willingness to accumulate, manage and sustain datasustain data

Examples:Examples:

CustomerCustomer SupplierSupplier

ProductProduct RegionsRegions

LocationLocation Corp Balance Corp Balance SheetSheet

ServicesServices

Business Value & ROIBusiness Value & ROI

How much will a new technical solution How much will a new technical solution cost? How much will we need to make cost? How much will we need to make to offset this cost?to offset this cost?

Is it soft money or hard dollars?Is it soft money or hard dollars? Will it take a change in staff or Will it take a change in staff or

business processes?business processes? Will our customers and/or users be Will our customers and/or users be

impacted?impacted? Will it provide better service? Quality? Will it provide better service? Quality?

Accuracy? Customer relationship?Accuracy? Customer relationship?

Data Governance Data Governance

Data Governance Council/Executive SponsorData Governance Council/Executive Sponsor– Business Functional Management (data owner) responsible for the acquisition and mgmt Business Functional Management (data owner) responsible for the acquisition and mgmt

of a key subject area of data on behalf of the corporationof a key subject area of data on behalf of the corporation Enterprise ArchitectEnterprise Architect

– Technical leadership responsible for developing the data stewardship strategy and Technical leadership responsible for developing the data stewardship strategy and visionsvisions

Data ArchitectData Architect– Technology leadership responsible for implementing the data stewardship strategy, Technology leadership responsible for implementing the data stewardship strategy,

understanding data dependencies and relationships and manage the data lifecycleunderstanding data dependencies and relationships and manage the data lifecycle Business Data StewardsBusiness Data Stewards

– Subject Matter experts who define the business data definitions, process, the maintain Subject Matter experts who define the business data definitions, process, the maintain the business definitions on behalf of a companythe business definitions on behalf of a company

IT Data StewardsIT Data Stewards– Technology delegates of the data owners or custodians who technically implement the Technology delegates of the data owners or custodians who technically implement the

business data definitions and administer the technical aspect of the data asset on behalf business data definitions and administer the technical aspect of the data asset on behalf of the corporationof the corporation

Data CreatorsData Creators– Employees who are authorized to create data as part of their jobsEmployees who are authorized to create data as part of their jobs

Data CustodiansData Custodians– Employees who have the authority to govern access to key data areasEmployees who have the authority to govern access to key data areas

Data UsersData Users– Employees who have been granted authorized access to Company information assets Employees who have been granted authorized access to Company information assets

to do their job.to do their job.

Data GovernanceData Governance

Data Governance Council/Executive SponsorData Governance Council/Executive Sponsor– Business Functional Management (data owner) responsible for the acquisition and mgmt Business Functional Management (data owner) responsible for the acquisition and mgmt

of a key subject area of data on behalf of the corporationof a key subject area of data on behalf of the corporation Business Data StewardsBusiness Data Stewards

– Subject Matter experts who define the business data definitions, process, the maintain Subject Matter experts who define the business data definitions, process, the maintain the business definitions on behalf of a companythe business definitions on behalf of a company

Data CustodiansData Custodians– Employees who have the authority to govern access to key data areasEmployees who have the authority to govern access to key data areas

AgendaAgenda

Defining Master Data ManagementDefining Master Data Management Three Aspects of MDMThree Aspects of MDM

– Knowledge (Business Context)Knowledge (Business Context)– Content Content – MaintenanceMaintenance

Business Needs vs. I.T. Business Needs vs. I.T. ExpectationsExpectations

MMD

Master Data ContentMaster Data Content

MetadataMetadata Transformation RulesTransformation Rules Data OwnershipData Ownership Meta Model with RelationshipsMeta Model with Relationships

MetadataMetadata describes how, when and by whom a particular set of data was collected. It also captures how the data is formatted, and if any transformations were applied to the data along the way.

BusinessBusiness– Business DescriptionsBusiness Descriptions– AKA ( Also Known AKA ( Also Known

As)As)– Business RulesBusiness Rules– Valid ValuesValid Values– Semantic LayerSemantic Layer– OwnershipOwnership– ReportingReporting– Data DictionariesData Dictionaries– Quality Control RulesQuality Control Rules– Change ControlChange Control

TechnicalTechnical– Physical LocationPhysical Location– Source to target Source to target

transformationstransformations– Physical CharacteristicsPhysical Characteristics– Key constraintsKey constraints– IndexesIndexes– Data ModelsData Models– Audit RulesAudit Rules– Retention informationRetention information– Table join Table join

recommendationrecommendation– User SecurityUser Security

Transformation RulesTransformation Rules

Documented changes, aggregations or Documented changes, aggregations or adjustments to data as it is moved from one adjustments to data as it is moved from one source to target locationsource to target location

Inclusions or Exclusions of information that Inclusions or Exclusions of information that might be mistakenly assumed as part of a might be mistakenly assumed as part of a totaltotal

Agreed upon by producers as well as Agreed upon by producers as well as consumers of the dataconsumers of the data

Data OwnershipData OwnershipRole Influence Accountability

Data StewardData Steward

Responsible for the acquisition Responsible for the acquisition and management of a key and management of a key subject area of data on behalf of subject area of data on behalf of the Corporation the Corporation

Highest level of Business Highest level of Business influence influence

Ensures information usage is aligned Ensures information usage is aligned with Corporate business strategy.with Corporate business strategy.

Promotes awareness and support of Promotes awareness and support of existing environments.existing environments.

Identifies and allocates business Identifies and allocates business resources required to implement new resources required to implement new data acquisitions.data acquisitions.

Approve data access and usage policies.Approve data access and usage policies. Identify and approve data custodians.Identify and approve data custodians.

Data CustodianData Custodian

Subject matter experts that Subject matter experts that define and maintain business define and maintain business data definitions and processes. data definitions and processes. Also define and implement Also define and implement security policies for business security policies for business unit data. unit data.

High level of influence. High level of influence.

Subject matter experts for a given set of Subject matter experts for a given set of business processes and definitions.business processes and definitions.

Assist in development and rationalization Assist in development and rationalization of corporate business definitions and of corporate business definitions and calculations.calculations.

Define and maintain business rules.Define and maintain business rules. Define and maintain security Define and maintain security

classifications.classifications. Ensure appropriate training on usage of Ensure appropriate training on usage of

data.data. Provide data quality improvement Provide data quality improvement

recommendations.recommendations. Knowledge experts for projects requiring Knowledge experts for projects requiring

similar data.similar data. Approve user access to business function Approve user access to business function

data.data. Prioritize enhancement requests to Prioritize enhancement requests to

shared data stores.shared data stores.

Meta Model with Meta Model with

RelationshipsRelationships Models

AgendaAgenda

Defining Master Data ManagementDefining Master Data Management Three Aspects of MDMThree Aspects of MDM

– Knowledge (Business Context)Knowledge (Business Context)– Content Content – MaintenanceMaintenance

Business Needs vs. I.T. Business Needs vs. I.T. ExpectationsExpectations

MMD

Master Data Master Data MaintenanceMaintenance Defining I.T. Support ModelDefining I.T. Support Model Identifying relevant measurable Identifying relevant measurable

MetricsMetrics Valid Value RulesValid Value Rules Defining a workable RoadmapDefining a workable Roadmap

Defining IT Support Defining IT Support ModelModel

More than Help DeskMore than Help Desk ITIL?ITIL? SOA?SOA? SCA?SCA? IEEE?IEEE?

Master Data Subject Master Data Subject MetricsMetrics

Key Subject Areas by Metrics

Quality Fair Poor Poor Poor Good Poor

Number of Sources 5 7 5 20 10 20

Steward or Owner Defined Name of ?? ?? N Name of ??

Conceptual Model Exists Y N N N Y N

Logical Model Exists N N N N Y N

Physical Meta Data Exists N N N N N N

Maintenance Standards in Place N N N N N N

Analytics Available N N N N Y N

Overall

Relevant MeasuresRelevant Measures

With the business identify what With the business identify what constitutes successconstitutes success– countscounts– qualityquality– retrievabilityretrievability

Report response time?Report response time? Minimal Redundancy?Minimal Redundancy?

Valid Value RulesValid Value Rules

Are they programmatically Are they programmatically enforced?enforced?

Does I.T. or the business maintain?Does I.T. or the business maintain? Determine how to measureDetermine how to measure

– AccuracyAccuracy– CompletenessCompleteness– ConsistenceConsistence– Business Rules violationBusiness Rules violation

Defining a workable Defining a workable roadmaproadmap

Back to the basicsBack to the basics– Identify subject areas that matter to Identify subject areas that matter to

the businessthe business– Determine how much time, Determine how much time,

resources and money you have to resources and money you have to accomplish your goalsaccomplish your goals

– Align the vision and execution of Align the vision and execution of support to ongoing projects in the support to ongoing projects in the queuequeue

AgendaAgenda

Defining Master Data ManagementDefining Master Data Management Three Aspects of MDMThree Aspects of MDM

– Knowledge (Business Context)Knowledge (Business Context)– Content Content – MaintenanceMaintenance

Business Needs vs. I.T. Business Needs vs. I.T. ExpectationsExpectations

MMD

MDM – Business vs. I.T. MDM – Business vs. I.T. ExpectationsExpectations

Business NeedsBusiness Needs– SpeedSpeed– Cost EfficiencyCost Efficiency– Business ValueBusiness Value– Competitive Competitive

AdvantageAdvantage– A sense of A sense of

urgencyurgency

I.T. NeedsI.T. Needs– Reasonable Lead Reasonable Lead

TimeTime– Cost EfficiencyCost Efficiency– Usable across orgUsable across org– Someone to pay Someone to pay

for the for the technologytechnology

– Someone willing Someone willing to define to define requirementsrequirements

Key Take AwaysKey Take Aways

Collaboration between business and IT Collaboration between business and IT essentialessential

Identifying what Master DataIdentifying what Master Data MattersMatters to to your business is critical your business is critical

Determine what Governance level your Determine what Governance level your organization needs and staff accordinglyorganization needs and staff accordingly

Be clear about expectations Business & I.T.Be clear about expectations Business & I.T. Metadata, Metadata, Metadata!!!Metadata, Metadata, Metadata!!!

References/ResearchReferences/Research

http://msdn2.microsoft.com/en-us/architecture/bb190163.ashttp://msdn2.microsoft.com/en-us/architecture/bb190163.aspxpx

A good overview of MDM, with some fundamental stepsA good overview of MDM, with some fundamental steps http://www.rainingdata.com/products/soa/mdm/index.htmlhttp://www.rainingdata.com/products/soa/mdm/index.html Challenges of Enterprise data versus Master Data mgmtChallenges of Enterprise data versus Master Data mgmt http://www.soamag.com/I4/0207-1.asphttp://www.soamag.com/I4/0207-1.asp - good article on SOA - good article on SOA

– also see model on slide 15 – also see model on slide 15 http://xml.coverpages.org/ni2005-12-07-a.htmlhttp://xml.coverpages.org/ni2005-12-07-a.html - Describes - Describes

in detail a service component architecturein detail a service component architecture http://http://www.conceptdraw.com/en/sampletour/uml_erdwww.conceptdraw.com/en/sampletour/uml_erd// (great (great

downloadable samples)downloadable samples) http://searchcrm.techtarget.com/generic/0,295582,sid91_gcihttp://searchcrm.techtarget.com/generic/0,295582,sid91_gci

1148946,00.html1148946,00.html – excerpt on valid values and data strategy from Sid – excerpt on valid values and data strategy from Sid Adelmann and Larissa MossAdelmann and Larissa Moss

Thanks for your time Thanks for your time and Interest!and Interest!

Dawn MichelsDawn Michels Enterprise Information Architect Enterprise Information Architect Past Pres DAMA-MinnesotaPast Pres DAMA-Minnesota Past VP Chapter Services DAMA-IPast VP Chapter Services DAMA-I Adjunct Faculty Member College of St. Adjunct Faculty Member College of St.

CatherineCatherine Passionate Data ArchitectPassionate Data Architect

dawnmichels@Andersencorp.comdawnmichels@Andersencorp.com 651-264-7985651-264-7985

My backgroundMy background

Dawn Michels is the Enterprise Information Architect for Andersen Corporation, in Dawn Michels is the Enterprise Information Architect for Andersen Corporation, in Bayport Minnesota and has many years experience in relational database design, Bayport Minnesota and has many years experience in relational database design, across several DBMS and applications. She has developed many data designs and across several DBMS and applications. She has developed many data designs and modeling initiatives spanning the Insurance, Medical Devices, and Retail and modeling initiatives spanning the Insurance, Medical Devices, and Retail and Credit Card industries. Dawn has also worked for Guidant Corporation, Fair Isaac Credit Card industries. Dawn has also worked for Guidant Corporation, Fair Isaac Inc, and Minnesota Life Insurance and was the project lead at General Mills on Inc, and Minnesota Life Insurance and was the project lead at General Mills on their first Corporate Wide DW. This included data design, internal marketing as their first Corporate Wide DW. This included data design, internal marketing as well as hardware and software selection. To round out her professional career, well as hardware and software selection. To round out her professional career, Dawn is an adjunct faculty member at The College of St. Catherine, teaching Dawn is an adjunct faculty member at The College of St. Catherine, teaching courses in Mgmt Information Systems and Information Mgmt. She has spoken at courses in Mgmt Information Systems and Information Mgmt. She has spoken at five previous DAMA International Conferences on assorted topics of interest, and five previous DAMA International Conferences on assorted topics of interest, and is scheduled to speak at DAMA-I 2007 in Boston, Mass..is scheduled to speak at DAMA-I 2007 in Boston, Mass..

Dawn was the VP of Chapter Services for DAMA International from 2000-2002. Dawn was the VP of Chapter Services for DAMA International from 2000-2002. Before taking on that role, Dawn was President of DAMA Minnesota chapter for 3 Before taking on that role, Dawn was President of DAMA Minnesota chapter for 3 years, and VP of Education for DAMA MN, 3 years prior to that.years, and VP of Education for DAMA MN, 3 years prior to that.

She believes in sharing and mentoring to the best of her ability, as she considers She believes in sharing and mentoring to the best of her ability, as she considers the best way to continue to develop data architecture is through experience and the best way to continue to develop data architecture is through experience and learning from others experiences and networking with peers at all levels.learning from others experiences and networking with peers at all levels.