<Insert Picture Here> Master Data Management

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1 <Insert Picture Here> Master Data Management 김대준, 상무 Master Data Management Team

2 MDM Issues Lack of Enterprise-level data code standard Region / Business Function Lack of data integrity/accuracy Difficulty of daily-based Data Quality management Difficulty of managing lots of interfaces Lack of Enterprise Data Governance Framework Need of collaboration with business partners Sourcing, Manufacturing, Sales, Marketing etc.

3 Key considerations when engaging into MDM projects How does MDM fit into my enterprise application footprint? How do I solve the data quality challenge? What should be my MDM vision / end-state? How do I get there? Where do I start? How can I phase my deployment? What MDM style do I implement? How will my choice today impact my ability to evolve? How can I support apparent conflicting MDM requirements across data domains (Customer, Product, Financials, )?

4 Industry specific requirements Telco Utilities Media Retail, Rate Plan Pricing NRC Usage Meter reading Attributes Catalog Terms Consumer Goods Manufacturing High Tech CDRs Handsets POS Billing Accounts Service Accounts Service Instance Premise Meter Consumer Org/Division Subscriber Value Policies Loyalty Points Curriculum Child Objects Classes Behavior Contracts SKUs Employee Terrorist Orders Stores Student Hierarchies/BOM Service Request Counters Teacher Campaign Industry Variants Learnings Offers/Responses Product Asset Customer Consumer Legal Entities Supplier Site Financials Trust Household Security Credit Score Taxpayer Tax Citizen Account Tax Return Case Tuition Risk Financial Account Financial Services Public Sector Higher Education + Extensibility

5 Fragmented data in typical enterprise topology Ever proliferating island of information SFA Call Center Web site Fusion Apps Partner in disparate applications covering multiple channels, divisions & functions duplicated, incomplete, inaccurate, Key enterprise processes based on unclean / incomplete data (marketing, sales, service & customer retention activities, regulatory compliance, new product introduction, ) ERP 1 SCM HR Fusion Apps Legacy Analytics validity in question Error prone Integration Slow enterprise agility and innovation

6 Enterprise MDM solution where information is available as a service to operational & BI systems SFA Call Center Web site Fusion Apps Real-time / near real-time Master Data Middleware / Application Integration Architecture Real-time / near real-time Master Data Partner MDM ETL BI/DW MDM provides the ability to Consolidate/Federate master & shared information into one place Cleanse, de-duplicate and Enrich data centrally Distribute data as a single point of truth as a service to consuming applications, enterprise business processes and decision support systems ERP 1 SCM HR Fusion Apps Legacy ETL Integrated Best of Breed First brick of your SOA

7 Oracle MDM in an Enterprise Architecture Business Applications CRM Oracle MDM provides the ability to Consolidate/Federate master & shared information into one place Cleanse, de-dup and enrich data centrally Distribute data as a single point of truth as a service to consuming applications, enterprise business processes and decision support systems Extract Transform Load (ETL) Billing Custom Other ERP Legacy Integration Bus Data Stewards Real time/ Batch Master Data Master Data Management Customer Components of a Comprehensive Chart of Product Master Master MDM Strategy Location Accounts Master Financial Asset Master Master DQ DQ Alternate Hierarchies, Reporting, Analysis Analytics ETL Reporting BI/DW Planning Industry Business Users Analysis Financial Close (HFM) ETL

8 Oracle Enterprise Master Data Management Operational Systems Data Governance & Compliance Requests, Approvals, Workflow, Audit, Risk Management Analytical Systems SAP Operational MDM Analytical MDM DW Oracle EBS Customers Suppliers Products Financials Analytical Entities BI & Data Marts PeopleSoft Planning Legacy Oracle Customer Hub Oracle Product Hub Oracle Hyperion Data Relationship Management Financial Consolidation External Applications Oracle Fusion Middleware Budgeting

9 MDM Differentiation Hyperion Data Relationship Management Oracle Customer and Product Hub Hyperion DRM Entities Customer, Supplier, Product Ledger (Chart of Accounts, Cost Centers, Legal Entities), Others Schema Deep vertical schema Data model agnostic Mode Operational MDM Operational & Analytical MDM Typical User Interaction Lights Off (high level of automation) Lights On (interactive - business user tool) Typical User Data Steward Financial / LOB Business User Strengths CUSTOMER, SUPPLIER Build golden record of customer Cleanse and de-duplicate party data Survivorship rules Data quality Audit Capability Pre-built customer data management processes Robust and flexible party data model PRODUCT Build golden record of product Standardize product descriptions Push standardized product definitions from PLM to multiple global systems Leverage clean data to consolidate buying power CHART OF ACCOUNTS, COST CENTERS, LEGAL ENTITIES Advanced Hierarchy Management Business User interaction Versioning Control Audit Trail (who moved what where when) Inheritance, derivation, and default attributes Synchronize financial master data changes to subscribing systems

10 Key MDM Components Data Admin User Interface Consuming Apps: Marketing, Sales, Order Fulfillment & Provisioning, Contracts, Support, Financials, Billing, Legacy Apps, Cross-ref Data Cleansing Service Items Billing / Service Account Master Data Lifecycle Processes & Policies Security Visibility Privacy Data Matching Survivorship Cust. Account Contacts Relationships Hierarchies Enrich Merge/ Unmerge Audit/ History Services Schema Web Services Source System Mgt Publish & Subscribe Pre-built processes Integration MDM Data Quality Rules Data Cleansing Transformation & load Data Matching Data Cleansing Data Cleansing ETL Source 1 Souce 2 Source 3

11 Picking the right MDM style <Insert Picture Here>

12 Understand the Different Architectural Styles of MDM Consolidation Style Registry Style Coexistence Style Transaction Style Matches and physically stores consolidated view of master data. Updated after the event and not guaranteed up to date. For Reporting, Analysis and Central Reference Matches and links to create a "skeleton" system of record. Physically stores the global ID, links to data in source systems and transformations. Mainly for Real-Time Central Reference Matches and physically stores a consolidated view of master data. Publishes the consolidated view. Not usually used for transactions, but could be used for reference. For Harmonization Across multiple sources and recipients Matches and physically stores the up-to-date consolidated view of master data. Central authoring of master data. Acts as System of Record to Support Transactional Activity No Update of Source Updates Source data Variations in: 1. Degree of physical instantiation of master data 2. Nature and latency of interaction between the hub and spokes 3. Where master data is authored 4. Suitability for transactional and analytical applications Source: Gartner

13 Deploying in Phases <Insert Picture Here>

14 Sample Phasing JWALK GUI Base Information Base Information Id Details Id Details Address Detail Address Detail Blacklist Blacklist Account Base Account Base Account Base Account Base Acct Billed Details Acct Billed Details Dispute Contact Dispute Contact Preferred Account Preferred Account Service Base Service Base LPS LPS ICMS - LL ICMS - GSM Legend Phase 2b: Real time MDM feed Phase 2d: MDM master for interactions Data Migration & Quality External Source Phase 2a: Pull / Push MDM data Phase 2b: Real time DQ Phase 1: Batch Feed Business Process Integration MDM Master Data Hub Sales CRM Service Phase 3: CRM Data Integration Phase 5: CRM GSM/LL Integration Phase 4a: Initial Load of clean data Phase 2c: MDM feeds downstream systems in batch Marketing Div 1 Div 2 Div 3 Billing EDW OL Phase 4b: Real time integration Real Time Batch Comptel PPAS TAPIN DOC1 ODS RA FMS

15 Sample Phasing CRM Sales Service Marketing Data GSM LL Phase 2a: Pull / Push UCM data Phase 3: CRM Data Integration Phase 5: CRM GSM/LL Integration Business Process Integration Phase 4b: Real time integration MDM Master Data Hub Geneva Phase 2c: MDM feeds downstream systems in batch EDW OL Legend Real Time Batch Comptel PPAS TAPIN DOC1 ODS RA FMS

16 Oracle MDM Enterprise MDM solution that provides information as a Service to operational systems ETL SFA Call Center Web site Fusion Apps Partner Real-time / near real-time Master Data Middleware MDM BI/DW Real-time / near real-time Master Data ERP 1 SCM HR Fusion Apps Legacy ETL

17 Mastering Data Governance <Insert Picture Here>

18 Oracle Best Practice - Data Governance Framework Data Governance needs three interdependent components; Data Definition Data Control Data Quality Master Data Mgt. Policy : data governance processes must be followed Master Data Mgt. Process : CRUD, communication, conflict resolution Master Data Mgt. Organization : Data Owner, Data Steward Data Governance Framework Policies Processes Organization Data Governance is foundational to data integrity Scopes of Data Governance Framework Defining the data entities & attributes Defining the Object naming standard Defining the data entry standard (including validation & verification rule) Defining data access and security policy Data retention criteria (Survivorship rule) Defining business rules Defining data quality metrics Define the metrics of data quality Define DQ procedures (data duplication, identification, and resolution, merge/unmerge) Define reports to measure quality metrics

19 Data Governance Strategy case study Design and implementation of the governance model is a phased approach leveraging best practices, lessons learned from past efforts, and Key Data Entity (KDE) design teams comprising of business, IT, and vendor SMEs. Pre-Deployment Deployment Post Deployment Governance Framework Governance Scope Assessment Governance Best Practices Data Governance Strategy High Level Design Identify key data entities for governance scope Stakeholder identification and engagement Develop & ratify Governance framework Develop and ratify Governance process DG Design Team Detailed Design Determine data mgmt processes and tools Establish data controls in data mgmt processes Identify data stewards and owners for key data entities Prepare proposal for data governance model for key data entities Build Define data controls and data policy requirements Identify change management considerations Develop detailed operating model Ratify NetApp Governance Model KDE Design Team Cutover Detailed Governance Operating Model Policy Policy Governance Governance Structure Structure Governance Governance Process Process Roles Roles and and Responsibilities Responsibilities Governance Framework KDE Governance Design Implementation Plan & Communication Strategy Data Governance Council Governance Model

20 Thinking the MDM Vision <Insert Picture Here>

21 Oracle MDM Vision Operational Systems Oracle EBS Data Governance Model Telco & Utilities MDM Implementation Best Practices Financial Services Public Sector High Tech & Manuf. Master Data Management Solutions Enterprise Business Processes Retail & CPG Analytical Systems Data Warehouse PeopleSoft Siebel SAP Legacy Application Integration Architecture Web Services Import Workbench Customer Supplier Product Design Workbench Financials Asset Location Enterprise Schema & Shared Services Master Data Management Applications Organization Analytical Data Marts MDM Analytics Business Intelligence (OBI EE) Financial Consolidation Web Apps External Applications Data Integration Business Process Orchestration Metadata Management Registry Service Hierarchy Management Audit & Change Management Data Quality & Enrichment Profiling & Correction Oracle Fusion Middleware / MDM Foundation Identity Management Events & Rules Engine Planning Budgeting

22 Learning from our 500+ customers Customer Information Under NDA

23 Oracle MDM The key differences 1 Toolkit vs. Application with easy extension abilities 2 Implementation know how 3 Leader in Party, Product and Finacial Hubs 4 Large scale deployments 5 Rapid Deployment

24 Contact Reference 김대준 상무, MDM Solution Architects Phone: 김태호 Principal Consultant, MDM Solution Phone: Oracle MDM Solutions (Data Hubs) Customer Data Management

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