aaron zornes founder & chief research officer the cdi-mdm institute a.k.a. technical...

Aaron ZornesFounder & Chief Research

OfficerThe CDI-MDM Institutewww.The-CDI-MDM-Institute.com a.k.a.

www.tcdii.com

Technical Evaluation Criteria & Field Reports for CDI-MDM

Solutions

© 2007 The CDI-MDM Institute The-CDI-MDM-Institute.com

Solidifying Requirements for 3rd Generation CDI-MDM Solutions

Multi-entity hub capabilities

SOA/shared services architecture with evolution to “process hubs”

Sophisticated hierarchy management

High-performance identity management

Data governance-ready framework

MASTER DATA SEARCH

MASTER DATA

MODELING

MASTERDATA

APPLICATIONS

CDI-MDM

MASTER DATA

PREPAR-ATION

MASTERDATA

GOVERNANCEMASTER

DATAMOVEMENT

Global 5000 enterprises’ “multi-hub” scenarios mandate architectural/infrastructure approach to CDI-MDM

Aaron Zornes

Need to blend MODELING and GOVERNANCE


Master Data Management Applications

Data, process, & policy hubs CDI data hubs: Amdocs; DataFlux; IBM WCC; Initiate Systems; Nimaya;

Oracle CDH; Oracle UCM; Purisma; Siperian; Teradata MDM; VisionWare

PIM data hubs: Comergent Technologies; Extol; FullTilt Solutions; GXS; Hybris; i2 MDM; IBM WCC (formerly Trigo); Liaison Technologies; Oracle PIM Data Hub; Riversand; SAP NetWeaver MDM; TIBCO CIM

Financial integration data hubs: Hyperion Solutions MDM; MetaVante Hub; Teradata Integrated Risk Mgmt

Life sciences data hubs: Cegedim; Dendrite Others, e.g. citizen data hubs, privacy preference management hubs

Enterprise information management (EIM) frameworks Above All (Composite Application Platform); Attunity; BusinessObjects

(Data Integrator XI); Composite; Cordys; Data Foundations (OneData); DataLever; Denodo; Extraprise i2i Platform; Group/1 CDI Suite; Hewlett-Packard ZLE; Kalido; MetaMatrix; ObjectRiver MDM; TIBCO (Collaborative Information Manager)

Master reference data hubs AML reference masters ; Counterparty reference masters; Pricing

masters; Security reference masters; Vendors: Cicada, Data Foundations; Fidelity Compliance Hub; GoldenSource; Human Inference Blacklist Watch; Oracle Universal Pricing Master, TIBCO CIM

Off-the-shelf apps & accelerator frameworks that employ various master data technologies to create & maintain an

integrated set of master data entities such as party (customer/supplier/vendor) & product


Master Data Modeling/Data Governance

Data models Vendors: GoldenSource Data Model; IBM

Information Framework; Oracle Trading Community Architecture; Teradata LDMs; Universal Data Models

Metadata management Vendors: ASG Rochade; CA Platinum Repository;

IBM Business Reference Directory; Sypherlink Harvester

Methodology Vendors: Deloitte/Informatica; IBM Data

Governance Method1, TIBCO Accelerated Value Framework (AVF)

The various software tools used to model both reference & operational master data; the methodologies & lifecycle

tools to manage enterprise master data as an asset


Master Data Preparation

Data profiling Vendors: IBM WebSphere ProfileStage; Informatica Data

Explorer (formerly Evoke); Netrics Data cleansing

Vendors: Business Objects Data Integrator: Cleansing; Human Inference HIquality; IBM WebSphere Quality Stage (formerly Vality); Informatica Data Quality Workbench (formerly Similarity); Innovative Systems ; Netrics; Pitney Bowes/Group 1; Platon Address Doctor; Silver Creek Systems DataLens System; Sypherlink Learning Lexicon; Harte-Hanks Trillium Software

Identity Resolution/Identity Matching/Entity Matching Vendors: Acxiom AbiliTec; Austin Tetra; Dun & Bradstreet;

Experian TruVue; Identity Systems; Nimaya IdentitySync; Purisma; Stratature +EDM; Initiate Systems Identity Hub; Netrics; Silver Creek Systems DataLens System

The various software & managed service provider solutions which enhance the quality & enrich the content of master data entities such as a “unified customer view”

or “unified physician view”


Master Data Movement

Business process management (BPM) & rules engines Vendors: BEA AquaLogic Business Service Integration

platform (formerly Fuego); Ilog; Fair Isaac Blaze; Experio; TIBCO Staffware Process Suite

Data federation/distributed query; enterprise application integration (EAI); enterprise information integration (EII); extract, transform, load (ETL); global data synchronisation (GDS)

Vendors: Ab Initio; BEA AquaLogic; BusinessObjects Data Integrator; Composite Software; Cross Z Solutions; Data Mirror; Denodo; Exeros; GoldenGate Software; IBM WebSphere DataStage (formerly Prism); IBM WebSphere Information Integrator; Informatica PowerCenter; Information Builders; Initiate Systems Data Federation; Ipedo; MetaMatrix; Oracle WarehouseBuilder/Sunopsis; Pervasive Data Junction; SAS Warehouse Studio; Software AG (Enterprise Information Integrator); Sun SeeBeyond ICAN Suite; Sybase Data Integration Suite; Sypherlink; TIBCO BusinessWorks (EAI), TIBCO DataExchange (ETL) , TIBCO CIM (GDS); webMethods

The various middleware technologies used to perform the amalgamation of master data via aggregation,

propagation, replication, & synchronisation technologies


MASTER DATA SEARCH

Vendors: Attensity; ClearForest; BrightPlanet Deep Query

Manager; Convera Technologies RetrievalWare; Endeca (Information Access Platform); IBM WebSphere Information Integration Search (Venetica); Insightful Corp. InFact; Inxight Software SmartDiscovery Analysis Server

Exploratory search & search engines incorporating both structured & unstructured information for a variety of applications such as catalog management, deep web

search & enterprise search


“Top 10” CDI Evaluation Criteria

1. Data model2. Business services3. Identity management4. Data governance5. Architecture 6. Data management7. Infrastructure8. Analytics 9. Developer productivity10. Vendor integrity

Infrastructure fracas will escalate as mega app vendors rush to dominate business services/processes & data models as high ground


#1 Criteria = Data Model

Data model to support complex roles & relationships Party (customer, supplier, employee) & product Reference – including price, location Demographic profile – e.g., name, address, phone number,

marital status, etc.

Roles & relationships between parties – including B2B companyhierarchies & B2C householding

Additional related entities – e.g., entitlements, prices, & privacy preferences

Data heritage, change history & survivorship Industry-specific (vertical) extensions Ability to import industry standard or custom-built

data models – e.g., IBM IAA, IBM BDW, OASIS CIQ, Siebel CIF, Hogan CIS, Dendrite

Ability to support 3rd party hierarchy structures – e.g., D&B, Austin-Tetra

Vendor roadmap to “link” party & product domains Depth & breadth of data model – plus ability to adapt statically & on-the-fly – provide a solid CDI–MDM foundation


#2 Criteria = Business Services

External workflow engine & web services transaction support – e.g., business process management (BPM)

Rules engine E2E support with operational applications with

accelerators for complex transactions – e.g., new account origination & order to cash

Business semantic-driven horizontal customer processes – e.g. add party, change address, retire customers

“Best practice” templates for both horizontal & vertical customer – e.g., related processes

Compatibility with existing infrastructure investments – e.g., Tibco, MQ-Series, etc.

Standards – e.g., OMG’s Model-Driven Architecture (MDA), WS-Coordination, WS-Transaction, & BPEL

Vendor roadmap to process/policy hub solution via SOAFunctionality & extensibility of business services are critical

evaluation criteria for CDI-MDM solutions – longer term “process hubs” are the goal


#3 Criteria = Identity Management

Very high performance matching/aggregation/search Ability to generate or incorporate “universal” master

keys or global IDs Cross-reference management – e.g., 1:M support,

enforcement of cross-referencing Support for all identity types – e.g., individual, household,

organisation Change detection & event mgmt – e.g., propagation

& validation, in-doubt resolution Support for privacy regulations – e.g., California SB-168 for

remediation of SSN off public documents E2E data mgmt processes to enforce data quality Enable regulatory & privacy mandates Non-obvious/intrusive entity resolution

Smart matching plus effective human intervention – & automated actions – yield better identity management


#4 Criteria = Data Governance

Process design capture tools Accelerators for people, process & technology

integration – e.g., DG steering committees, process councils, & corporate/LOB data stewards

Tactical data steward consoles Integrated metrics

Based on recognition of issues at hand, an improving economy, & increasing regulatory requirements, businesses are now recognising the opportunity to take a more strategic view of data governance


#5 Criteria = Architecture

Multi-modality architectures Virtual/registry Persistence Confederation

Multi-modal use cases Analytical MDM Operational MDM Collaborative MDM

Multi-modal security Profile access control Integration with security of DB, CRM & ERP Role-based user rights mgmt

Given the generational evolution of CDI-MDM styles, it is vital to select a CDI-MDM solution specifically tuned

for a given set of long term CDI-MDM requirements


#6 Criteria = Data Management

Consolidation & survivorship rules – e.g., intelligent merge/unmerge

Application- & role-level authorisation Data cleansing

Address cleansing & standardisation Pre-built integration to leading DQ tools Closed loop-DQ Data profiling

Central enforcement & tracking of DQ Integration with Web-enabled aggregator data Complex, long running transaction Support for multiple master data types – e.g., reference,

transactions Comprehensive set of customer attributes for complete

profile History & audit trailsGoal is to create end-to-end data mgmt processes that may be

invoked by other major customer facing subsystems in addition to CRM package


#7 Criteria = Infrastructure

Scalability – e.g., in-memory or cache DBs; just-in-time aggregation

Manageability - e.g., system management & monitoring tools Accessibility – e.g., ability to service wide-range of performance

levels Availability – e.g., resilience to various failure situations such as

hardware & network outages; continuous data maintenance/ synchronisation

Rigorous multi-model support for all integration modes Real-time

Tightly-coupled – e.g., COM, Java, CORBA) Loosely-coupled (IBM MQ Series, XML/HTTP, integration servers)

Near real-time Loosely-coupled (IBM MQ AMI, XML/HTTP, integration servers)

Batch EDI, RosettaNet

Pre-packaged integration processes & templates Intelligent routing – e.g., alerts, content-based routing & pub-

subAs “single point of failure” asset, CDI-MDM internal infrastructure has all the requirements of mission-critical applications & must be

evaluated so


#8 Criteria = Analytics

Customer segmentation & targeting for cross-sell & up-sell

In-line analytics for closed-loop marketing Data profiling to manage “degree of trust”

associated with given master customer data source (e.g., completeness, uniqueness, accuracy, & lineage)

No longer are batch-oriented data marts or data warehouses sufficient to provide fundamental analytics necessary to drive

customer profitability & value assessments (to enable JIT & differentiated service)


#9 Criteria = Developer Productivity

Life-cycle approach Systems management tools

Change management Software distribution Testing

CMM compliance Methodology

CDI-MDM ultimate goal is user-driven rules management, yet IT professionals (data stewards, et al) must set up & fine-tune this

mission-critical infrastructure


#10 Criteria = Vendor Integrity

References vs. proof-of-concepts Professional services – Work done by IT vendor to assist in the

delivery of solution via methodology, process, skills transfer, etc. Quality Breadth Customisation

Corporate agility – Ability to respond, change direction, etc. in Responsiveness/Development Processes/Flexibility

Personnel – Mix of skills, expertise, experience, etc. Leadership/available skills Expertise/intellectual property

Financials – Combo of financial resources, liquidity, etc. Access to capital Profitability Growth rate

Vendor pricing models

CDI-MDM solutions have all the requirements of mission-critical applications – vendors must be evaluated so


Competitive Field Reports**

D&B Integration Mgr DataFlux Data Foundations

OneData Hyperion MDM i2 MDM IBM WebSphere

Customer Center Initiate Systems

Kalido MDM Oracle Customer Data Hub Oracle Universal Customer

Master Purisma Data Hub SAP NetWeaver MDM Siperian MDM Hub Teradata MDM VisionWare

** Persisted customer data hubs with minimum 5 installs


Field Report: D&B Integration Manager

Strengths Operational & Analytical

MDM Hub-extensible registry

style Pure CDI solutions – esp. mktg

departments Best-in-class matching for

business ID – e.g. match engine with B2B emphasis

Reference-based matching B2B hierarchy accelerator Hosting services available ~$100M aggregate revenue

within $1.7B DSP References – Cisco, EMC,

Microsoft Live, Oracle, Sun Microsystems, …

Weaknesses Active hierarchy

mgmt Lack of strong SI

channel Lack of vertical

strategy 2nd tier CDI-MDM

vendor alliances evolving

Under invested in marketing

Struggles to perform as S/W vendor

Performance / scaling


Field Report: DataFlux

Weaknesses High-end proof

point Minimal CDI-MDM

references Lack of SI channels Lack of

BPM/workflow for “policy hubs”

Strengths Integrated DQ Multi-entity data model SOA Modest data governance SAS “deep pockets” SAS channel Midmarket references –

American Heart Association, Aspect, Intrawest, StorageTek,


Field Report: Data Foundations OneData

Strengths Full lifecycle with DG

framework Integrated customer,

product & vendor master data

Data model flexibility Full SOA Focus on MDM &

reference data Sophisticated hierarchy

mgmt – relationship charts, rules mgmt

Price

Weaknesses Primarily a tool kit Lack of strong SI

channel Under invested in

marketing Lack of CDI

references


Field Report: Hyperion MDM

Strengths Analytical MDM Mature product

(due to Razza acquisition) Hierarchy mgmt for

reporting, performance mgmt, DW, …

Robust business rules engine

Intuitive change mgmt suitable for business users

Strength in financials Integration with HYSL

corporate performance mgmt apps & others

HYSL sales force as channel

Weaknesses Lack of CDI

references Uncertain MDM

future due to pending M&A by ORCL & subsequent fallout with SAP


Field Report: i2 Master Data Management

Strengths Full lifecycle Integrated enterprise

MDM – customer, product & vendor

Full SOA including reference workflows

Retail, mfg, PIM & vendor mgmt expertise

Data model flexibility Focus on MDM (10+ years

& over 1K implementations experience in data models, data semantics & data mgmt)

Separate division for Marketing & Sales MDM

Weaknesses Lack of strong SI

channel Under investment

in marketing = name recognition & market awareness issues

Lack of CDI references


Field Report: IBM WebSphere Customer Center

Weaknesses Data governance

strategy maturing BPM/EAI strategy is

maturing for process hubs

Registry strategy still maturing

“Forced fit” with WebSphere family (Product Center, Information Server)

Strengths MDM for analytical & operational SOA architecture provides

for hub swap-out Industry model expertise Momentum – AT&T, BankAmerica,

Barclays, Canadian Tire, CWI (Holland Workers Compensation), Irish Life, De Lage Landen/RABO, Mastercard, Norwich Union Life, Post Finance, …

High-end production sites – BCE, Citi, MetLife, …

IBM GBS channel + TCS & Wipro


Field Report: Initiate Systems Identity Hub


strategy missing including high performance rules engine & process hub

Persistence strategy still ramping up

SI channel ramping up – ANC, BE, IBM

Lack of integrated DQ

Strengths Fast time-to-value Real-time probabilistic

match scalability Public references –

Countrywide, Intuit, Microsoft, UPMC, …

Healthcare, hospitality & retail pharmacy expertise

50% growth in customer base


Field Report: Kalido MDM

Strengths Analytical MDM reporting Customer, product,

financial, supplier, employee, KPI, etc.

References – BP, Nationwide, Labatt, Owens Corning, Shell, …

Process flows for complex data governance

Focus on MDM for analytics & corporate performance mgmt

MDM methodology & workflow engine

Time variance support for change mgmt

Weaknesses Not focused on

operational MDM Lack of strong SI


marketing Enterprise DW

positioning vs. early MDM proponent

Performance / scaling (resolved in MDM 8R3?)


Field Report: Oracle Customer Data Hub

Weaknesses High-end references Fair-to-meek

customer recognition capability

Best fit is mid-market & B2B

Lack of industry-specific data models

Strengths Strong enterprise MDM vision Mid-market references – BBC-

TV, CIT Group, Co-Op, Etat De Geneve, GGB, Hanjin Shipping, Network Appliance , …

High-tech mfg expertise Trading community

architecture Global ID generation, mgmt &

x-ref Integrated DQ & analytics Future integration with Oracle

DB


Field Report: Oracle-Siebel Universal Customer Master


strategy just evolving – at tactical data stewardship level

Shifting roadmap for future integration of hubs, & also with apps

Intelligent batch load scaling issues**

Strengths Strong enterprise MDM

vision First to mkt with process

hub (Privacy Management Policy Hub) Momentum & expertise in

telco & retail banking High-end production sites –

Endesa, Home Depot, UMB Bank, TFS, … Integrated DQ & analytics Strong SI channel Future Oracle DB

integration

**Resolved by Oracle Data Integrator (a.k.a. Sunopsys)


Field Report: Purisma Data Hub

Weaknesses Lack of strong SI


marketing Scarce references

Strengths B2B, B2C, & B2B2C

hierarchy management Global ID capability Appliance model Data governance

accelerator Strong partnerships

with D&B & Business Objects


Field Report: SAP NetWeaver Master Data Management

Weaknesses Operational MDM

lacking M/W only for transport Batch-like SAP XI required

for data movement “Customer” data type

still maturing No party-based data

model ... “business partner” ≠ customer

MDM 5.5 sp4 data model does not support party concept

Only simple 2 layer hierarchies

Matching works but no AUTOMERGE

Strengths Analytical MDM

reporting Quantity of MDM references

– Adidas, Intel, Nortel, Whirlpool, …

Supply chain expertise PIM focus – product information

management Image management (catalog

publishing) SAP underpinnings for

change mgmt


Field Report: Siperian MDM Hub

Strengths Field-tested multi-entity

support – Products/Customers– B2B/B2C/B2B2C– Employee/Contractor/Clinical Protocol/Product

Multiple implementation architectures

Federated architecture + high-speed match & link

Strong partnership with Identity Systems

Pharma & financial services expertise/momentum

Weaknesses Entity lifecycle mgmt

– esp. data governance

SI & data service provider partnerships still maturing

Under invested in marketing

Perceived as “pharma-centric”


Field Report: Teradata Master Data Management

Strengths Analytical + Operational

MDM Full lifecycle & process flows

for multi-entity support Proven data models with

industry expertise – Banking, Insurance, Retail, Telco, Travel & Transportation

Consolidated platform for EDW & MDM as unified/single repository of enterprise master data = lower TCO

Integrated risk management

Weaknesses Missing formal CDI

solution Operational data

governance strategy evolving

Minimal references given it is a new solution


Field Report: VisionWare MultiVue Identification Server

Strengths Analytical + Operational

MDM People, property & assets Public sector expertise Sophisticated, yet well-

packaged core MDM functionality – e.g., DB partitioning, web services, BPM

Mid-market pricing MSFT software stack

affinity MSFT as channel 100+ installations

Weaknesses Strategy beyond public

sector just beginning Currently mid-market

scalability – e.g., millions vs. 10s of millions of master records

Matching algorithms require odious manual intervention

Operational data governance strategy evolving

Registry-orientation more than persisted data hub


Bottom Line

Acknowledge that no single vendor “does it all well” Analytical vs. Operational vs. Collaborative

MDM B2B vs. B2C vs. B2B2C Batch vs. real-time

Recognise that industry expertise matters

Test drive matching & consulting expertise

Apply data stewardship tools for business users for long-term data sustainability

aaron zornes founder & chief research officer the cdi-mdm institute a.k.a. technical...

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