The document discusses different techniques for building a Customer Data Hub (CDH), including registry, co-existence, and transactional techniques. It outlines the CDH build methodology, including data analysis, defining the data model and business logic, participation models, governance, and deliverables. An example enterprise customer data model is also shown using a hybrid-party model with relationships, hierarchies, and extended attributes.

1. Database Architechs Customer Data Hub methodology August 2009 – Master Data Management

3. Co-existence Technique

4. Transactional TechniqueCDH Build Methodology (within a Development Life Cycle) CDH Deliverables along the way Customer Data Hybrid data model Enterprise customer example

5. Business Processes & Systems Sales Marketing Sales Service Fulfillment Leads Market Quotes Service / Support Fulfillment Contacts / Responses Opportunities / Deals Orders Registration / Activation Renewals ERP Call Center CRM/PRM Whitespace Quote Generation Order Mgmt Credit Mgmt Product/Pricing Invoicing/Billing Credit Card Proc Account Mgmt Auto Fulfillment Financial Mgmt Human Resources Contract/Agreement Management Opportunity/Lead Mgmt Direct Sales Channel Sales - Partner Center - Deal Reg Mgmt Campaign Planning Customer Profiling Service/Contracts Sterling EDI Mktg Apps Renewal Opty (int/channel) Partner Center (service) Customer Segmentation & List Generation Marketing Campaigns Marketing Performance Cleansing/De-duping Lead Routing Predictive Modeling Forecasting AOE ERPAssets Mgmt, Entitlements, Procurement Single OE eStore Orders Credit Card Processing Sub Center Sub Customers Service Requests Agreements, Contracts Electronic Fulfillment, Activation/Registration Incentive Programs Master Data Account/Contacts/Partner and then Product/Pricing, Workforce, others) (Identity Management Business Services/Web Services – SOA Data Delivery Platform (Real-time ODS , Aggregation Layer, Analytics, Predictive Modleling)

6. Business Processes & Systems (DATA) Sales Marketing Sales Service Fulfillment Leads Market Quotes Service / Support Fulfillment Contacts / Responses Opportunities / Deals Orders Registration / Activation Renewals CONTACT CUSTOMER CUSTOMER OPPORTUNITY LEAD OPPORTUNITY PROSPECT Account Parent (Company) PARTNER PRODUCT & PRICING ORDERS QUOTES Campaign/ Event DEALS ASSETS/ENTITLEMENTS CUSTOMER PROFILE/SEGMENTATION CONTRACTS / AGREEMENTS SUBSCRIPTIONS REGISTRATIONS/ACTIVATIONS SALES TERRITORY/GEO COMP PLANS/QUOTAS COMMISSIONS

8. Customer Data Hub’s by Segment Consumer 360 ° Customer Transaction Views Customer ID Mgmt Enterprise Sales Entity Customer Service Customer Loyalty Partner/Channel Etc. Analytics Views Real Time Analytics “Other” Historical Analytics

10. Cross Reference Only (attributes not mastered in hub)

11. Provides links to sources (that may not share the same data model)

12. Non-invasive (easier to implement, but less attribute consistency)DW Historical Analytics DM

14. Cross References and Golden Record stored at hub

15. Maps attributes to common data model

16. Extended Attributes

17. High Attribute consistencyDW Historical Analytics DM

19. Cross References and Golden Record stored at hub

20. Maps attributes to common data model

21. Extended Attributes

22. High Attribute consistency, High cross systems consistencyDW Historical Analytics DM

23. CDH Build Methodology Data Analysis/Data Assessment (spokes) 1 Data Analysis/Master Data Model (hub) 2 Broader Architecture Spoke Define Business logic/workflow 3 1 Integration Identify/Define participation model 4 Outbounds 1 Hub Inbounds Overall/Broader architecture participation 5 1 2 3rd party service 3 Define Governance, Stewardship, business org 6 4 1 1 Build/Deploy 7 1 5 7 6

25. Use cases/Data accesses

26. Volatility/Frequency/Velocity

27. Data Quality assessment

29. Standards being applied

30. Logic being applied

31. What we have and what we need Broader Architecture Spoke 1 Integration Outbounds 1 Hub Inbounds 1 3rd party service 1 1 1

41. Party-based mappings (hub/spoke)

42. Cross Reference Identities/Registry

43. Ownership model

44. Data Models (hub/spokes)

46. Merge, match, Dedupe logic

47. standardization, cleansing

48. Data sync needs

49. Mappings/context

50. Transformations needed

51. Logical/physical merge approach

53. Contributing Attributes from each spoke to the hub

54. overall publishing/subscribing needs (frequency/volatility)

56. CDH Build MethodologyEnterprise Customer Phase I Broader Architecture Aprimo Accounts Contacts Integration Hub Accounts Match Publish Subscribe Enrich ABC.com DNB (enrichment) Accounts Contacts Trillium (Cleansing & Match) Siebel/CRM Next Spoke

57. Enterprise Customer (Hybrid-Party Model) Relationships Hierarchies Hierarchy Level Hierarchy Types Product Authorization Product Authorization Types Product Authorization Groups Agents/Partners Relationship Types Account Contact Contact Roles Contact Role Types Parties CONTACT (Person) ACCOUNT (Organization) GROUP Account Role Types Account Roles Customer Account Contact Profile Account Profile Contact Preferences Account Types Account Type Types Customer Account Site External Enrichments (D&B, etc) Agreement Role Types Agreements Agreement Contacts Agreement Role Location GEO Unit GEO Unit Relationship Geo Structure Geo Level - R17 R18 TBD R17

58. Enterprise Customer example Org (Party) Highest level Sales Entity “General Electric” “102099994” Person (Party) Hierarchy “Parent to Subsidiary” “Jane Doe” Org (Party) “General Electric – Corporate” “Contact” “45669994” Party Org (Party) “Parent to Subsidiary” “General Electric – Satellite Div” “DUNS#” “100022” “SFDC Reference” “64909977” “ERP Customer # (Bill to)” “DUNS#” “Partner/Channel (sell thru)” Extended Attributes “3689” Org (Party) “342990667” “IM2990699” “29903689”

59. Questions? Send me emails at: pbertucci@dbarchitechs.com