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2 Oracle Enterprise Data Quality Overview and Roadmap Martin Boyd Senior Director, Product Strategy Mike Matthews Director, Product Management 2

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. 3

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

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. 5 Ken Orr, The Cutter Consortium

6 Data Changes in the Real-World Companies Individuals Products 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 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 On average 20% duplicates in product data 90% product introductions fail Retailers lose $40B or 3.5% of total sales 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 Master data changes at a rate of 2% per month 6 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 With Bad Data With Good Data Reduced ROI Increased project risk, time and cost Expensive downstream consequences wrong shipment, wrong invoices, incorrect parts Increased ROI on existing systems Increased agility Increased efficiency Increased customer satisfaction Increased scalability 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 Data integration and data quality are fundamental prerequisites for the successful implementation of enterprise applications, such as CRM, SCM, and ERP. 7

8 Typical Customer/Party Data Issues Variation or Error Example Sequence errors Mark Douglas or Douglas Mark Involuntary corrections Concatenated names Nicknames and aliases Noise Abbreviations Browne Brown Mary Anne, Maryanne Chris Christine, Christopher, Tina Full stops, dashes, slashes, titles, apostrophes Variation or Error Transcription mistakes Missing or extra tokens Foreign sourced data Unpredictable use of initials Transposed characters Hannah, Hamah Example George W Smith, George Smith, Smith Khader AL Ghamdi, Khadir A. AlGamdey John Alan Smith, J A Smith Johnson, Jhonson Wlm/William, Mfg/Manufacturing Localization Stanislav Milosovich Stan Milo Truncations Credit Suisse First Bost Inaccurate dates Prefix/suffix errors Spelling & typing errors MacDonald/McDonald/Donald Transliteration differences 12/10/1915, 21/10/1951, , Gang, Kang, Kwang P0rter, Beht Phonetic errors Graeme Graham 8

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 = RPM 115V 48YZ YOKE MTR Item Motor Classification Power 10 horsepower Voltage 115 Mounting Yoke Motor, TEAO, 1725 RPM, 48YZ, 15 Voltios, Montaje de Yugo, hp = 10 9

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

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

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

13 Improve Data, Improve App Performance Govern Protect Parse/ extract Standardize Enrich Verify Match/ merge Gold data Fit for purpose data Improve Apply data standards Metrics, KPIs Understand 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 13

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

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

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

17 Oracle Data Integration Complete Offering for Enterprise Data Integration Legacy Applications OLTP Unstructured Oracle Data Integrator Oracle GoldenGate Oracle Enterprise Data Quality Oracle Data Service Integrator 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 Modernization Custom MDM BI Big Data Synchronization SOA 17

18 Common Access/UI 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 Standardize Drive conformance to standards Global parse Category parse Extract Transform Address verification & geocoding Substitute Enrich Classify Profile Quickly understand data content Enterprise DQ Platform Statistics Patterns Phrases Duplicates Completeness Max/min values 18

19 Common Access/UI Enterprise Data Quality Enterprise DQ Cloud Services Enterprise DQ Matching Cloud Service Enterprise DQ Address Verification Cloud Service Govern Monitor effectiveness & resolve problems Match Identify & merge duplicates Standardize Drive conformance to standards Profile Quickly understand data content Enterprise DQ Platform 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 19

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

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 o o One-time cleanse/migration Ongoing governance program Features Hierarchical Case/alert functionality Configurable Workflows Automatic prioritization of cases/alerts Timers Notification Support Comprehensive audit trail Immediate ad-hoc reporting 21

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 Legacy Data EDQ Process Fit for Purpose Data 22

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

24 EDQ Investment Areas Integrated DQ & Governance Integration Across Oracle Cloud/SaaS Global Rules & UI Advanced Techniques Integrated best-inclass Customer and Product DQ Deeper Siebel Integration SaaS deployment for Fusion Apps Global Identity Resolution Statistical parsing & classification Expand Governance to include operational confidence reporting Out-of-the-box DQ for Fusion Apps Full clustering and elastic provisioning support DQ Rules and Reference Data for major locales Statistical outlier detection Integration with ODI Cloud DQ Services Additional UI Localizations Entity identification & extraction for Big Data Endeca, ATG, EBS 24

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 25

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

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 27

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 28

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 29

30 EDQP 11 - Major Features New Integrations Connector for Endeca Guided Navigation Integrated with Agile PLM 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 30

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

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 32

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

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 3 rd 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 34

35 Join the Data Integration and MDM Community Twitter Facebook Blog LinkedIn YouTube blogs.oracle.com/dataintegration blogs.oracle.com/mdm 35

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