MDM Is Not EnoughMDM Is Not EnoughSemantic Enterprise IsSemantic Enterprise Is

by Semyon Axelrodby Semyon AxelrodSemanticWebEnterprise SemanticWebEnterprise

semyonax@semanterprise.comsemyonax@semanterprise.com

““The significant problems we face today cannot be solved at the The significant problems we face today cannot be solved at the same level of thinking we were at when we created them.same level of thinking we were at when we created them.””

Albert EinsteinAlbert Einstein

““By far the most common mistake is to treat a generic situation By far the most common mistake is to treat a generic situation as if it were a series of unique events, that is, to be pragmatias if it were a series of unique events, that is, to be pragmatic c

when one lacks the generic understanding and principle.when one lacks the generic understanding and principle.””

Peter Ferdinand DruckerPeter Ferdinand Drucker

AgendaAgenda•• Modern Enterprise modus operandi Modern Enterprise modus operandi

•• Integration of disparate information systems Integration of disparate information systems

•• IssuesIssues–– Data integration versus system integration Data integration versus system integration

•• Data Integration Techniques and TechnologiesData Integration Techniques and Technologies•• Master DataMaster Data

–– Modern enterprise complexityModern enterprise complexity–– Lack of business processes architectureLack of business processes architecture

•• SolutionSolution–– Enterprise ArchitectureEnterprise Architecture–– Semantic Enterprise Semantic Enterprise

•• Q&AQ&A

Integration in the modern Integration in the modern enterpriseenterprise•• No business is static No business is static –– the only constant is the only constant is

changechange•• Business processes and business systemsBusiness processes and business systems

–– Integration crosses existing enterprise boundariesIntegration crosses existing enterprise boundaries•• PartnersPartners•• SuppliersSuppliers•• ClientsClients•• VendorsVendors

•• New systems are being built and legacy systems New systems are being built and legacy systems are being modified are being modified

•• All systems need to be connected All systems need to be connected –– integratedintegrated

Data and Systems Integration Data and Systems Integration •• Theoretical Perspective: Data integration is the process Theoretical Perspective: Data integration is the process

of combining data residing at different sources and of combining data residing at different sources and providing the user with a unified view of these data providing the user with a unified view of these data –– Maurizio Lenzerini, "Data Integration: A Theoretical PerspectiveMaurizio Lenzerini, "Data Integration: A Theoretical Perspective””. Principles of Database Systems (PODS) . Principles of Database Systems (PODS)

symposium (2002).symposium (2002).

–– Works well for OLAP and in case where operational context is Works well for OLAP and in case where operational context is highly homogeneous and thus can be standardized highly homogeneous and thus can be standardized •• US Postal AddressUS Postal Address

•• Practical Perspective: Systems interoperability is based Practical Perspective: Systems interoperability is based on the exchange of data between systemson the exchange of data between systems–– Works well for OLTP Works well for OLTP

•• For this presentation:For this presentation:Data integration Data integration ≡≡ Systems integration Systems integration

Data Integration Techniques and Data Integration Techniques and TechnologiesTechnologies•• Techniques Techniques –– technology independent technology independent

approaches/styles:approaches/styles:–– Propagation, Consolidation, FederationPropagation, Consolidation, Federation

•• Technologies Technologies –– practical implementations practical implementations of techniques:of techniques:–– Data Replication, ETL, EAI, EII, ECMData Replication, ETL, EAI, EII, ECM

•• Tools Tools –– COTS applicationsCOTS applications–– Colin White, Colin White, ““A roadmap to Enterprise Data A roadmap to Enterprise Data

IntegrationIntegration””, BI Research, November 2005, BI Research, November 2005

Modern Enterprise Information Flow Modern Enterprise Information Flow

International

ODS 2

ODS 1

Enterprise

DataWarehouse Product Development

Marketing

GL1

GL

Long Term Trend Analysis

NorthAmerica

MasterData

Sales

MDM MDM –– integration perspectiveintegration perspective•• Master Data is shared data that has a single content and Master Data is shared data that has a single content and

format and is available to all the systems within the format and is available to all the systems within the enterprise that need to reference it enterprise that need to reference it –– ProductProduct–– Supplier Supplier –– CustomerCustomer

•• Master Data Management (MDM) is the capability to Master Data Management (MDM) is the capability to create and maintain a single, authoritative source system create and maintain a single, authoritative source system of of ““mastermaster”” enterpriseenterprise--level data. level data.

•• MDM application (or system) is a system that provides MDM application (or system) is a system that provides consistent view of dispersed data. consistent view of dispersed data. –– Colin White, Colin White, ““A roadmap to Enterprise Data IntegrationA roadmap to Enterprise Data Integration””, BI , BI

Research, November 2005Research, November 2005

MDM MDM –– semantic perspectivesemantic perspective

•• It is always possible, and arguably, quite It is always possible, and arguably, quite easy, to misinterpret any shared data in easy, to misinterpret any shared data in the absence of rich contextual information the absence of rich contextual information that unambiguously distinguishes between that unambiguously distinguishes between different possible meanings different possible meanings –– CustomerCustomer

•• Current customerCurrent customer•• HighHigh--value customervalue customer•• Returning customerReturning customer

Master Data Management as Master Data Management as semantic integration problemsemantic integration problem

•• Customer for different operational unitsCustomer for different operational units–– SalesSales–– MarketingMarketing–– Customer ServiceCustomer Service–– LegalLegal–– Regulatory Operational RiskRegulatory Operational Risk

•• Primary BorrowerPrimary Borrower–– Primary Financial v Primary Legal Primary Financial v Primary Legal –– Origination, Secondary Acquisition, Risk Analysis, Primary ServiOrigination, Secondary Acquisition, Risk Analysis, Primary Servicing, cing,

Investor Servicing, etcInvestor Servicing, etc

•• Bankruptcy IndicatorBankruptcy Indicator–– Legal Legal –– Operational as used in loan servicing Operational as used in loan servicing

Senseless Conclusions or Senseless Conclusions or Meaningful Integration Meaningful Integration •• ““Integrating two Integrating two ““lossloss”” relations with (implicit) relations with (implicit)

heterogeneous semantics leads to erroneous results and heterogeneous semantics leads to erroneous results and completely senseless conclusions. Therefore, explicit and completely senseless conclusions. Therefore, explicit and precise semantics of integratable data are essential for precise semantics of integratable data are essential for semantically correct and meaningful integration results.semantically correct and meaningful integration results.””

•• ““Note that none of the integration approaches above Note that none of the integration approaches above helps to resolve semantic heterogeneity; neither is XML helps to resolve semantic heterogeneity; neither is XML that only provides structural information solution.that only provides structural information solution.””–– Three decades of data integration Three decades of data integration –– all problems solved?all problems solved?

Chapter 4, from Structural to Semantic IntegrationChapter 4, from Structural to Semantic IntegrationPatrick Ziegler and Klaus R. Patrick Ziegler and Klaus R. DittrichDittrich. University of Zurich. . University of Zurich.

Modern Enterprise ComplexityModern Enterprise Complexity

•• ScaleScale–– Local Local globalglobal

•• Time Time –– Significant latency Significant latency NRTNRT

•• TechnologyTechnology–– Ubiquitous and omnipresent Ubiquitous and omnipresent –– Operational Silos Operational Silos EnterpriseEnterprise--level viewlevel view–– Static applications with substantial manual steps Static applications with substantial manual steps

Composite applications and SOAComposite applications and SOA--type servicestype services

SolutionsSolutions

•• Business processes contextual information Business processes contextual information contains the answers that we are looking contains the answers that we are looking forfor

•• Data and Process Data and Process –– yin and yangyin and yang

Semantic reconciliationSemantic reconciliation•• Vickie Farrell, Vickie Farrell, CerebraCerebra WebMethodsWebMethods Software AG:Software AG:

““Lack of "semantic reconciliation" among data Lack of "semantic reconciliation" among data from different sources is inherent in a diverse, from different sources is inherent in a diverse, dynamic and autonomous organization. dynamic and autonomous organization. ……Resolving discrepancies in metadata descriptions Resolving discrepancies in metadata descriptions from multiple tools, not to mention cultural and from multiple tools, not to mention cultural and historical differences, involves more than historical differences, involves more than physically consolidating metadata into a physically consolidating metadata into a common repository.common repository.””““The Need for Active Metadata Integration: The HardThe Need for Active Metadata Integration: The Hard--Boiled TruthBoiled Truth””, ,

DM Direct, September 2005; http://www.dmreview.com/dmdirect/200DM Direct, September 2005; http://www.dmreview.com/dmdirect/20050909/103670350909/1036703--1.html1.html

EA: 4 Domains and 3 PerspectiveEA: 4 Domains and 3 Perspective

I

Yin and Yang of Information ManagementYin and Yang of Information Management

Business Capability

1

Business Capability

4

Business Capability

3

Business Capability

2

Principlesand

Heuristics

Computationally Independent Business Capabilities Domain

Conceptual Enterprise Information Model

Business Strategy

Platform Specific Physical Implementation Domain

TechnologyStandards

and Guidelines

Enterprise System B

Specification

Enterprise System A

Specification

EnterpriseIntegration

Model

Enterprise ITGovernance Framework

Platform Independent System Specification Domain

XML SchemasDB Schema/Tables

Components Business Services

Logical Enterprise Information Model

LOB-Level Systems

Interfaces

Physical Enterprise Information (a.k.a. Data) Model

ITILCMDB

Technology Services

MDAMDA--inspired Architectural Domains Iinspired Architectural Domains I

MDAMDA--Inspired Architectural Domains IIInspired Architectural Domains II

Semantic EnterpriseSemantic Enterprise•• WellWell--engineered business enterprises engineered business enterprises

–– ProcessProcess--driven informationdriven information--centric and contextcentric and context--richrich–– WellWell--defined Governance defined Governance –– CoCo--evolution between business and ITevolution between business and IT

•• Enterprise ArchitectureEnterprise Architecture–– Unifying organizing logic at the enterprise levelUnifying organizing logic at the enterprise level–– Develops and maintains all EA domainsDevelops and maintains all EA domains

•• Uses modern approaches to address the issues long termUses modern approaches to address the issues long term–– Ontologies and other semantic technologiesOntologies and other semantic technologies–– Domain modeling Domain modeling –– SOA basedSOA based

•• MDAMDA

Semantic Enterprise Technologies Semantic Enterprise Technologies -- OntologiesOntologies

•• OntologiesOntologies–– Ontology in addition to taxonomy Ontology in addition to taxonomy

characteristics, with formal characteristics, with formal subtypingsubtyping and and rules for inclusion and exclusion, will also rules for inclusion and exclusion, will also include other relationships, i.e., part ofinclude other relationships, i.e., part of•• UML diagrams: Class, Activity, State Transition UML diagrams: Class, Activity, State Transition

Diagrams, etcDiagrams, etc

Semantic Enterprise Technologies Semantic Enterprise Technologies ---- SOASOA

•• Enterprise SOA Governance should include Enterprise SOA Governance should include EnterpriseEnterprise--level ontologies level ontologies –– Semantic technologies (OWL, RDF) should be part of Semantic technologies (OWL, RDF) should be part of

the SOA technology suite along with UDDI, WSDL, etcthe SOA technology suite along with UDDI, WSDL, etc–– Service repositories and registries should be able to Service repositories and registries should be able to

handle ontological operations in addition to UDDIhandle ontological operations in addition to UDDI–– Semantic of each service operation should be Semantic of each service operation should be

completely unambiguous from both operational and completely unambiguous from both operational and informational perspectivesinformational perspectives

Semantic Enterprise Semantic Enterprise –– where to startwhere to start

•• Culture changeCulture change•• Use models Use models •• UMLUML•• Business capabilities model Business capabilities model

–– Information modeling instead of data Information modeling instead of data modelingmodeling

–– Connecting business success to EAConnecting business success to EA

Q&AQ&A

•• semyonax@semanterprise.comsemyonax@semanterprise.com•• ??