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I4E MDM Architecture Sadagopan Krishnamachari IBM


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MDM Architecture Sadagopan Krishnamachari IBM in Information Excellence Presentation in 2011 August

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I4E MDM Architecture Sadagopan Krishnamachari IBM

  1. 1. MDM Architecture and ImplementationBest PracticesSadagopan Krishnamachari © 2008 IBM Corporation
  2. 2. Agenda  Fragmented Data Problems …  Master Data & Master Data Management  IBM Infosphere Master Data Management Server  MDM Server Implementation Pattern  MDM Architecture  MDM Data Stewardship Application  MDM Search / Matching Algorithm2
  3. 3. Islands of InformationReduce customer satisfaction, decrease revenue, hinder relationships Online Direct Purchases Mail Response Internet CRM Commerce Marketing Michael Johnson Michael Johnson ! Opt-Out flag User id :mjohnson ! No Promotion flag JP Morgan Contract:: JP987 Application Online Forms Registration Document Portal Management Service and 3rd Party In-Store Payments Support Information Interactions Michael Johnson Michael Johnson User ID: Mjohnso Mortgage.tif ERP CRM Data Retail Point ! Personalized access Call Center Warehouse of Sale ! Gold Customer JP Morgan, USA JP Morgan & Chase Mike Johnson Michael P Johnson ! Sub: Newsletter 1 Cust ID : JP003 Contact : Michael A JP Morgan Chase 1400 54rd Avenue Johnson, CIO NY NY Last Interaction: 270 West St, NY 4/11/03 (product not 212 995-3345 received)37
  4. 4. Inconsistent Master Information is a Major HurdleImpacts Revenue, Cost, Agility and Compliance CH, AUT, DE, UK, FR, BEL, NL, IT : DE, FIN, SWE, NOR, ESP, POR, Code : 21184 Code : 21190 CAN Code : 21204 BUL, YUG, CR, RO, SLOV Gaining control over product information results: Code : 19616  Errors in data – 30% of data in retailers systems is wrong CZ, LIT, EST, SLOV, RU  Lost productiv ity – 25 minutes manual cleansing per SKU, per year Code : 2002494  Slow time to market – 4 weeks to introduce new products  Inv oice deductions – 43% of invoices result in deductions  Failed scans – up to 70,000 per week (1 large US Retailer)  Lost sales – up to 3.5% per year Source: A.T. Kearney, GMA, AMR USA Code : 21192  Industry Driv ers: RFID, Waste Electrical and Electronic Equipment Recycling, Product Information Exchange Standards, Return JAP, THAI, INDO, PHI of Hazardous Substances, Code : 21189 Global Data Synchronization, Sarbanes Oxley, etc. (Yankee Group, 2005) ISR Code : 21204 HK, TAI, SIN, MAL, S.KOR Code : 21188 Coffee Beans GTIN BR, CR, MEX 20012294219421 Code : 21186 MidEa Code : 21204 ARG Code : 21184 World Trade AUS Code : 19619, 19616 Code : 2119046
  5. 5. Master Data Facts describing the core business entities: customers, suppliers, partners, products, materials, bill of materials, chart of accounts, location and employees •The high value information an organization uses repeatedly across many business processes •Generally used across multiple LOBMaster Data Management Master Data Management (MDM) is the set of disciplines, technologies and solutions to create and maintain consistent, complete, contextual and accurate business data for all stakeholders across and beyond the enterprise5
  6. 6. MDM Repository / Hub is analogous to a Version Control System,albeit for your Master Data6
  7. 7. MDM Server Implementation Environment Management Vendor & Other W eb Phone Call Center Sales Business Partners Process Server InfoSphere M DM Server InfoSphere MDM Data Stewardship Business Services (e.g. Siebel) (e.g COGNOS) Real-time Pre- buil t Cust omi zable MDM Domains Real-time/Near-Real-Time Connectivity Services (ESB, EAI, Web Services, MQ, etc.) Party Account Product C ustom RDBMS Integratio n Content Dat a Analy tic s IBM InfoSphere MDM Server Billing/ Corporate New Systems Order Service & Others (e.g. SOA –based) Provisioning External Data Security, Content Providers (e.g. Management Enterprise Mail, etc D&B, ACXIOM, Data Warehouse/ Data MartCustomer Customer Customer Customer Experian) Product Product Product Product Account Account Account Account Others Others Others Others Enterprise Data Integration (InfoServer) Master Data Batch Load Understand Cleanse Transform Deliv er7
  8. 8. The Complete Picture – Multi Form MDM Server Banking Insurance Government Healthcare Retail Telco Focused on critical information intensive business problems IBM Master Data Management Multiform Master Data Management Collaborate Operationalize Analyze Multiform MDM manages data domains critical to business Industry Models & Assets processes Party (Customer, citizen, prospect, organization, supplier, distributor, etc.) Product (good, service, product bundle, catalogue, product component, etc.) Account (Agreement, financial account, reward program, etc.) ETL Tooling Unified Deployment Multiform MDM Understand Cleanse Transform Deliver leverages merged, cleansed and standardized Unified Metadata Management data via the ETL8
  9. 9. MDM Consumers Common Components D ata Java A dmin E SB / M Q / D as hboard/ C lient Stewardship Classes Web A pp E A I Broker P ortal U Is A pplications Web A pp E xternal Bus iness Rules Rules Rule Engine Sets Web M es saging Batc h E vent E vergreen Services A dapter P roc essor M anager P roc essor A dapter E xternal Validators Validation V alidation Rules Web Services As ynchronous Synchronous Client-Defined I nterface Adapters Request Framework E vent M anager Events Service Controller P arser XM L Notifications Request H andler N otification JMS T opic C omposite C onstructor T ransaction Bus iness Transaction Manager H andler Bus iness Proxies Sec urity C onfiguration Configuration M anager Settings Extension Framework MDM Core Rules of Data-Level Business Admin Party Contract History Fast V isibility Entitlements Java Services Services Services Services Services Track Classes T ransaction Audit Pre/Post Audit Data E xtension Txn C ontroller Components I nformation L og Rules Engine C ontroller Pre/Post Action P erformance ARM Bus iness L ogic C omponents T rac ker Agent Rule Sets E rror Behavior Extensions Utility Suspect Processing Error Standardization M es saging Messages Components Components Extension L ogging W CC Co r e Code Operational History Logs E xtension Tables Tables Tables Tables T oolkit Data Rule Data Data History Data M etaData Metadata Data ExtensionsMDM 8.0 MDM Product Component Common Component 3rd Party Product Client Component Significant Pluggable Component9 2008Jan,
  10. 10. MDM Workbench – A Model based Data Model10
  11. 11. Data Stewardship Application – Duplicate Suspect Processing11
  12. 12. Matching and Searching Algorithm Data Derived Hash Buckets Step 1: Optimizes data for statistical comparisons Robert RBT 121213444 – Normalizes & compacts data, creates derived data layer source data remains intact Potter PTR 34839020 – Phonetic equivalences, tokenization, nicknames, etc. Step 2: Finds all the potential matches Name ZIP SSN – Casts a wide net – all matches on current or historical attributes, 1222 3456 3421 prevents misses 2222 6666 3333 3334 5435 3555 – Partial matches, reversals, anonymous values, etc. Step 3: Scores accurately via probabilistic statistics – Compares attributes one-by-one and produces a weighted score (likelihood ratio) for each pair of records – Frequency weights specific to your business – Edit distance, proximity of match 8.63 Step 4: Custom threshold settings Should be linked – Single or dual threshold models 7 9 Should not be linked – Link, don’t link, don’t know – “learns” from manual input Lowest Highest Don’t possible Manual review Link possible score link score Lowest Upper threshold threshold12
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  14. 14. Extras14
  15. 15. Useful Links IBM Information On Demand website ( IBM Information Management website ( Extreme Leverage website ( Customer Success Stories ( Information Management Demos ( Information as a Service Demo ( Videos (