Oracle Enterprise Data Quality Overview and Roadmap

2. Oracle Enterprise Data QualityOverview and Roadmap Martin Boyd – Senior Director, Product Strategy Mike Matthews – Director, Product Management

3. The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.

4. Program Agenda • Why Care About Data Quality and Governance? • Oracle Enterprise Data Quality • Roadmap and Demonstration

5. “Ultimately, poor data quality is like dirt on the windshield. You may be able to drive for a long time with slowly degrading vision, but at some point, you either have to stop and clear the windshield or risk everything.” Ken Orr, The Cutter Consortium

6. Data Changes in the Real-World Companies Products Individuals In one hour… In one hour… In one year… • 240 businesses will change addresses • 150 business telephone numbers will change or be disconnected • 112 directorship (CEO, CFO, etc.) changes will occur • 20 corporations will fail • 12 new businesses will open their doors • 4 companies will change their name • On average 20% duplicates in product data • 90% product introductions fail • Retailers loose $40B or 3.5% of total sales lost each year due to item master inaccuracy • 60% of all invoices will have an error • Companies with global data Sync will realize 30% lower IT costs • 5,769 individuals in the US will change jobs • 2,748 individuals will change address • 515 individuals will get married • 263 individuals will get divorced • 186 individuals will declare a personal bankruptcy Master data changes at a rate of 2% per month Source: D&B, US Census Bureau, US Department of Health and Human Services, Administrative Office of the US Courts, Bureau of Labor Statistics, Gartner, A.T Kearney, GMA Invoice Accuracy Study 6

7. Business Impact of Data Quality “Data integration and data quality are fundamental prerequisites for the successful implementation of enterprise applications, such as CRM, SCM, and ERP.” ” “Only 30% of BI/DW implementations fully succeed. The top two reasons for failure? Budget constraints and data quality.” “#1 reason CRM projects fail: Data Quality”

8. Typical Customer/Party Data Issues

9. Typical Product/Item Data Issues 10hp motor 115V Yoke mount MOT-10,115V, 48YZ,YOKE mtr, ac(115) 10 horsepower 115volts This 10hp yoke mounted motor is rated for 115V with a 5 year warranty 10 Caballos, Motor, 115 Voltios TEAO HP = 10.0 1725RPM 115V 48YZ YOKE MTR Motor, TEAO, 1725 RPM, 48YZ, 15 Voltios, Montaje de Yugo, hp = 10

10. Putting your Data to Work Common Data Quality Use Cases • Application Enablement • Clean-up and govern application data (CRM, HR, PLM, Retail search, etc.) • System Consolidation/Migration • Enforce new system standards on legacy data • MDM Enablement • Verify, standardize, match and and merge data from disparate sources • Business Intelligence Enablement • Enforce BI standards on disparate data • Compliance • Drive consistent data and processes to meet regulatory requirements (watchlist screening, anti-money laundering, tax compliance, etc.)

11. Data Quality – Is Your Data “Fit for Purpose”? • How do you know? • What is the business impact? • What should you do about it?

12. Your Data Health Check – Is Your Data “Fit for Purpose”? Govern Business & data standards • Understand current data ‘fitness for purpose’ • Estimate DQ impacts & ROI • Identify critical issues & quick wins Protect Current issues, gaps, errors Improve Your Experts Understand

13. Improve Data, Improve App Performance Parse/ extract Enrich Match/ merge Govern Stand-ardize Verify ‘Gold’ data Fit for purpose data • Improve ROI and performance of existing applications • Engage users and executives • Bring data to a known, baseline quality – ready to roll-out new applications and initiatives Protect Metrics, KPIs Improve Apply data standards Understand

14. ‘DQ Firewall’ – Continuous Protection for Information Assets External sources/ feeds Govern Hub • Continuous, consistent enforcement of standards • High quality data drives ROI • No more DQ projects! Data Integration/ETL Non-DQ/MDM-aware Apps Protect DQ/MDM-aware Apps Web service call Improve Apply data standards/validate Understand

15. DQ Governance – Continuous Process Improvement Source system DQ metrics Govern • Monitor ongoing effectiveness • Track and resolve issues • Improve overall effectiveness DQ process metrics ‘Gold’ data Protect Target system DQ metrics Apply data standards Improve Understand

16. Program Agenda • Why Care About Data Quality and Governance? • Oracle Enterprise Data Quality • Roadmap and Demonstration

17. Oracle Data Integration Complete Offering for Enterprise Data Integration • Complete and best-of-breed approach for enterprise data integration • Maximum performance with lower TCO, ease of use and reliability • Certified for leading technologies to deliver fast time to value Oracle Data Integrator Legacy Oracle GoldenGate Applications Oracle Enterprise Data Quality OLTP Oracle Data Service Integrator Unstructured Modernization Custom MDM BI Big Data Synchronization SOA

18. Enterprise Data Quality Enterprise DQ Cloud Services Enterprise DQ Matching Cloud Service Enterprise DQ Address Verification Cloud Service • Packaged cloud services for cloud applications Govern Monitor effectiveness & resolve problems • Process metrics • Quality metrics • Case Management • Remediation Match Identify & merge duplicates • Party (individuals, households) match • Entity match • Semantic (category) match • Statistical match • Match review • Merge/survivorship Common Access/UI Standardize • Global parse • Category parse • Extract • Transform • Address verification & geocoding • Substitute • Enrich • Classify Drive conformance to standards Profile • Duplicates • Completeness • Max/min values • Statistics • Patterns • Phrases Quickly understand data content Enterprise DQ Platform

19. Enterprise Data Quality Enterprise DQ Cloud Services Enterprise DQ Matching Cloud Service Enterprise DQ Address Verification Cloud Service • Broadest DQ offering • Best of breed capabilities for both Party Data and Product Data • Profiling, standardization, matching, case management, governance • Most usable DQ offering • Completely integrated offering – designed to work together • Designed for business and technical users • Transparent operation and results – no black boxes • Pervasive operation for enterprise quality governance • Within legacy systems and MDM Hubs • As part of migration/system load • On data entry/capture • As part of data movement/transfer Govern Monitor effectiveness & resolve problems Match Identify & merge duplicates Common Access/UI Standardize Drive conformance to standards Profile Quickly understand data content Enterprise DQ Platform

20. EDQ Web Services Enforce common DQ standards across the enterprise App 1 App 2 App 3 Applications • Any EDQ process may be called as a real-time web service • Call any process from any application to • Enforce common standards • Minimize architectural changes Library of enterprise standard DQ services Common Services

21. Case Management for Governance Review and resolve exceptions from the DQ process • Usage • Cases/alerts are assigned a work queues and a priority • Data specialists sign in and review/resolve issues • Management reports allow monitoring of work queues and productivity • Helpful for • One-time cleanse/migration • Ongoing governance program • Features • Hierarchical Case/alert functionality • Configurable Workflows • Automatic prioritization of cases/alerts • Timers • Email Notification Support • Comprehensive audit trail • Immediate ad-hoc reporting

22. Data Prep for System Migration/Implementation Governance and Case Management to ‘Perfect’ Data • DQ Insight (Dashboard) • Reporting • Trend Analysis • Case Management • Workflow • Remediation Apps and hubs EDQ Process Legacy Data ‘Fit for Purpose’ Data

23. Program Agenda • Why Care About Data Quality and Governance? • Oracle Enterprise Data Quality • Roadmap and Demonstration

24. EDQ Investment Areas

25. EDQ in the Cloud Cloud Data Services powered by EDQ • Providing data enhancement services in the Oracle Cloud • Uses EDQ as the matching engine and to ensure reference data quality EDQ in Fusion Apps • EDQ to be deployed and used by Fusion Apps • Leveraging Oracle DB and FMW cloud support EDQ in Managed Cloud • Growing number of customers already choosing to run full service EDQ in the Oracle Managed Cloud EDQ powering Partner Cloud Offerings • Kaygen partnering with Oracle to deliver Data Governance in managed cloud with EDQ • Several others following suit

26. EDQ for Fusion Applications Enterprise DQ Cloud Services Enterprise DQ Matching Cloud Service Enterprise DQ Address Verification Cloud Service Govern Monitor effectiveness & resolve problems Match Identify & merge duplicates Common Access/UI Standardize Drive conformance to standards Profile Quickly understand data content Enterprise DQ Platform • Fusion Applications Integration (Fusion R9) • EDQ deployed in Fusion Apps as the attached DQ engine • Advanced Search, Duplicate Prevention, Master Data Matching • Address Verification and Cleaning for all countries

27. EDQ 11 - Major New Features • Case Management Expansion • Instant reports on high volume data • Aggregated reports (e.g. activity by period, priority, etc.) • Improved case search and filter • Expanded workflow options • Reference Published Processors • Enables development of ‘locked’ IP to extend EDQ • Full reuse and upgrade of processors across processes/projects • UI Localization to 9 Languages • Chinese, Japanese, Korean, Brazilian Portuguese, French, Italian, German, Spanish, English

28. EDQ 11 - Improving Productivity • New Job Manager • User-defined job layouts and canvas notes • ‘Blocking’ triggers allow jobs to be called within jobs with execution control • Additional externalization options • New Process Canvas • Improved canvas usability and multi-language support • Browser-based Web Service Tester • Faster testing of EDQ Web Services

29. EDQ 11 – Other Changes • Oracle Universal Installer • Automated installation process for all platforms • Fusion Middleware Integration • Enables use of WebLogic OPSS for security and authentication • Uses FMW Audit Control to capture key configuration changes • Automated Results Purge capability • Support for Subversion 1.7 • Array support in Data Interfaces • Multi-attribute data type converters

30. EDQP 11 - Major Features • New Integrations • Connector for Endeca Guided Navigation • Integrated with Agile PLM 9.3.2 • Statistical Matching Module (StatSim) • Quick Rules Free Configuration • Match or classify verbose semi-structured data • Integrated with Governance Studio • Remediation Capabilities • Provides List of Values for Data Enrichment • Integrated with AutoLearn Workflow

31. Client Browser Data Source Data Source Data Source EDQP Drives Endeca Navigation Improved data improves user experience Integrated Data Quality: • Populate – Identify, extract and standardize product dimensions & properties • Integrate – Automatically create required dimensions within Endeca (avoid manual dimension setup) Data Preparation Endeca Load Endeca Engine EDQP PIM or any other data source EDQP ‘pushes’ required metadata into Endeca to create required navigation dimensions • Standardize data structure • Standardize data values • Integrated directly into Endeca pipeline

32. EDQ 12c • Data Quality Governance II • Integrated Semantic Data Engine (EDQ-P) • Full WebLogic Server Clustering support • Shared config for multiple EDQ servers • Session balancing and failover • Active-Active Case Management • Oracle Access Manager integration • Hadoop Connectivity • Fully automatable Reference Data Generation

33. Data Governance with EDQ Current capabilities to be enhanced and combined into a new cloud-enabled DQ Governance UI • DQ Insight (Dashboard) • Reporting • Trend Analysis • Case Management • Workflow • Remediation Enabling People and Process with Technology Data sources DQ Engine Apps and hubs Single DQ environment Real-time checks

34. EDQ Application Integration Enabling Applications with Data Quality Services • Fusion Applications – Deep integration in progress; planned for Fusion R9 release • Siebel CRM and UCM– Deep integration in place using services architecture; more stable, performant, functional and scalable than 3rd Party or OEM integrations • EBS – Template connectors available for common integrations (customer/party, etc.) • Salesforce.com – Template connectors available for batch cleansing • Oracle Product Hub; Fusion Product Hub – Deep integration for batch and real-time load • ENDECA (Oracle Commerce) – Data cleansing and metadata sync to streamline managing complex product data schemas for eCommerce • Agile PLM – Template connectors for batch and real-time validation, BOM validation and BOM sync • Application owners are painfully aware of the impact & costs of poor data • EDQ is investing heavily in providing out-the-box Application DQ solutions

35. Demonstration

36. EDQ 11 – Reference Published Processors EDQ enables the construction, publication and packaging of domain-specific processors that can be packaged and reused on any EDQ server Functionality has now been extended to support use by reference as well as copy, allowing the construction of locked and upgradeable processors in many projects EDQ Solution Development are already using this to build a set of reusable processors for customer data in various locales

37. Reference Published Processors • Construct a new processor by configuring a chain of processors • Configure how to expose inputs and options • Reference data may be packaged inside the processor or ‘expected’ by it • Add a family and custom icons • Publish to the server: - Choose ‘Template’ or ‘Reference’ • Package to create formal processor packs

38. EDQ 11 – Case Management Improvements • Instant searching and operational reporting for large data volumes • Aggregations in reporting • Search on history • Find all cases commented on by me • Find all cases transitioned in workflow by me • Use negative search logic • Find all cases where value is NOT x

39. EDQ 11 – New Job Manager User-specifiable layouts Externalization of all major configuration points to allow dynamic overrides Improved UX and performance Improved trigger controls Canvas notes

40. EDQ 11 – Additional Localizations • All UIs available in: • US English • French • Italian • German • Spanish • Chinese • Japanese • Korean • Brazilian Portuguese

41. Q&A

42. Join the Data Integration and MDM Community Twitter Facebook Blog LinkedIn YouTube blogs.oracle.com/dataintegration blogs.oracle.com/mdm