Oracle Data Profiling and Quality 11gR1


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Oracle Data Profiling and Quality 11gR1 e-Seminar

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Oracle Data Profiling and Quality 11gR1

  1. 1. <Insert Picture Here> <I t Pi t H >Oracle Data Profiling and Quality 11gR1Oracle PartnerNetwork EnablementUgo Pollio, Principal Sales Consultant, DIS EMEAFX Ni l Nicolas, Principal P d t M P i i l Product Manager, DIS
  2. 2. Agenda g• Introduction to Data Quality• Oracle Data Profiling and Quality Overview• Data Quality Use Cases• Demonstration D t ti• Q&A
  3. 3. IntroductionData Quality
  4. 4. Managing the Information Sensitive Business Value of Trusted Information Why do I have so Why are my many duplicate Why can’t I get applications copies of data? access the data I referring to last Much of it is need for decision week’s numbers? inaccurate! making ? Accessible Up-to-Date Trusted Information Information Information• Available • Fast access • Accurate• Secure • Multiple sources • Consistent• Reliable • Actionable • Quality
  5. 5. What is Data Quality? y• Degree of Excellence of the Data• Process of making and keeping data in a state of completeness, validity, consistency, timeliness and accuracy that makes it appropriate for a specific use.
  6. 6. Example of Data Quality Issues p y Matching Records Non Standard formatsName Address City State Zip Phone EmailBob Williams 36 Jones Avenue Newton MA 02106 617 555 000 bob.williams@yahoo.comRobert Williams 36 Jones Av. MA 02106 617555000Burkes, Mike and Ilda 38 Jones av. Nweton MA 02106 617-532-9550 mburkes@gmail.comJason Bourne, 76 East 51st Newton MA 617-536-5480 6175541329Bourne & Cie.… … … … … … … Mis-fielded data Multiple Names Mixed business Typos and contact Missing Data names
  7. 7. Two Facts about Data Quality y Clear view on data• The Data Quality Challenge is an iceberg • The biggest DQ threats are the ones we do not see. gg Q Data Profiling lowers the water line and draws a clear view of the quality issues Risk manageable Business rules tractable Known Data Issues Expectations clear E t ti l High business user involvement Suspected Data Issues Unexpected Data Issues Risk unmanageable Business rules unknowable Missed expectations Mi d t ti Little business user involvement
  8. 8. Two Facts about Data Quality y Data quality decays• Data value decays • Data is an asset which value decays over time y • Business events can make this worse • Quality is not a one shot p y process but a constant effort in the enterprise processes. Data Quality needs to be pervasive and continuous. Pervasive Oracle Data Integrator Supplies Standard, Inline Data Quality and Data Profiling Capabilities with Every ETL and E-LT Job Continuous Oracle Data Profiling and Oracle Data g Quality for Data Integrator support Integrated Workflow, Recycling, and Steward GUIs
  9. 9. OverviewData Profiling & Quality
  10. 10. Oracle Data Quality Products y• Oracle Data Integrator • Integrate Data between sources and targets with inline data g g integrity check • Call Data Quality processes• Oracle Data Profiling • Investigate quality issues• Oracle Data Quality for Oracle Data Integrator • Cleanse, Parse, Match & Merge , , g• Oracle Product Data Quality • Semantic Approach to product data quality
  11. 11. 1. Investigate - Oracle Data Profiling g g ODP/ODQ Client • Profiling/Investigation • Quality monitoring • Investigate the Data • Structure • Content • Values, statistics, Sampling & S li frequencies, frequencies ranges Analysis Metabase • Data Relationships • Dependencies, keys, p y joins • Assess Data Compliance • Report & Alerts • Monitor Quality Over Time
  12. 12. 2. Cleanse - Oracle Data Quality y ODP/ODQ Client • Quality Project Design • Rules Tuning • Proven, scalable DQ engines • Rich global content for cleansing, standardization, validation Metabase • Packaged Quality Rules • Delivered Out-of-the-Box Out of the Box by Oracle • For 60+ Countries • Extensible & Customizable Rules Route Parse Match Link MergeData Quality Server
  13. 13. 3. Run with Oracle Data Integrator g Oracle Data Integrator • Moves & Transforms Data • Integration handled by • Calls Quality Processes ODI • Advanced quality processing handled by ODQQ • Pre-built Knowledge Modules • For Metadata Exchange • Tool for DQ process invocation Route Parse Match Link MergeData Quality Server
  14. 14. What’s New in ODP/ODQ 11gR1 g• Business Rules Library• User-Defined Templates User Defined• Enhanced International Support • Multi lingual client (user interface for design environment) Multi-lingual • Tuning facilities for global data, including double-byte data• Improved Geographic Support • E.g.: Expanded Japanese Postal Matcher Options • Latitude/Longitude appends Globally appends, Globally.• User Interface Enhancements
  15. 15. Data QualityUse Cases
  16. 16. Data Quality for Business Intelligence Change Data into valuable Information • The Business Issue • BI Reports are not trustable, because of the state of source data DO NOT • Reduce risks TRUST THIS • Improve data q p quality by integrating y y g g DATA ! cleansing as part of the processProfiling• Investigate • Eliminate data redundancies Cleansing • Standardize, Enrich, Match • Improve Business Insights Control • Improved business insight with improved • Govern over time data quality q y • Better profiling of data to eliminate gaps in insight
  17. 17. Data Quality Dashboards in OBIEE yAttribute Analysis, Historical Analysis, DQ Stats
  18. 18. Data Quality Firewall y Profile, Repair, Check, Alert, Report Sources Database COBOL DQ Dashboard Copybooks Route Parse Match Link Merge Files• DWH, improving reliability and quality• New ERP/CRM installation, and legacy data Discarded integration Records R d• Master Data Management projects• Data synchronization projects Human Workflow
  19. 19. Data Quality for Migration ODP + ODQ + ODI CRM Route Parse Match Link Merge g COBOLCopybooks M&A Analyze Build & Test & g & Design Cleanse Validate MDM Iterations ERP 1 Assumptions 2 Identified Failure(s) DWH 3 Files Documentation Metadata Business InputToday Tomorrow The Truth Content Agreed Structure Plan (less risk) Scope Relationship Managed Resources Timescale Quality Productive Cost
  20. 20. Demonstration
  21. 21. Questions
  22. 22. For More Information Quote Attribution Title, Company Get Started Resources• Visit the Oracle Fusion Middleware 11g g • Datasheet: web site at ware/odi/docs/odiee-datasheet.pdf ex.html • Blog:• Oracle Data Integration on • Technical information available at:• Oracle Fusion Middleware on OTN ucts/oracle-data-integrator/index.html• Information on GoldenGate: • Data Integration Events