1. iWay Solutions - EIM Vincent Deeney – Solutions Architect 6/25/2009

2. Information Builders Agenda  Information Builders and iWay Software  Technology Overview  Demonstration Use-Case  Technical Demonstration

3. iWay Software Integration of all content –data warehouse, files, queues, CMS, documents, email, ERP, CRM, SFA. Support spectrum of all integration patterns ETL, SOA, B2B, MFT etc. Integrated data quality and master data management Enrich and feed business events and data extracts to operational data stores, data warehouses, applications, enterprise search engines Enable real-time dashboards, scoring and analytics through embedded complex event processing

4. Technology Overview iWay Software Enterprise Integration

5. A typical problem Receiving data in multiple formats from external partners (csv, txt, edi, etc.) Data of varying quality. Lack of visibility into full process (end-to-end). Various Manual Steps

6. Upstream Data  Data/Information Enters from Multiple Points  Manual Data Entry  B2B Gateway  Call Center  Self-Service Portal  EIM Issues  Accuracy  Completeness  Business Rule Validation  Correlation

7. In-stream Data  Data is a Flowing, Dynamic thing  Complex Processes  Derived Data  Evolving Semantics  Operational BI  EIM Issues  Error Detection and Correction  Lost or Mismatched Information  Duplication  Validation as Evolves

8. Downstream Data  Data is collected, manipulated, and analyzed  DM/DW/Cubes/Analytical BI  Performance Management  Compliance  Auditing  EIM Issues  Access  Accuracy  Completeness  Mismatched Semantics

9. Enterprise Information Management Requirements  Single View  Data Quality  Master Data Management  Operational Data Store  Customer Data Integration  Citizen Services  Master Patient Index  Product Information Management  Real Time Data Warehouse

10. Master Data Management Defined  MDM for customer data systems are software products that:  Support the global identification, linking and synchronization of customer information across heterogeneous data sources  Create and manage a central, database-based system of record  Enable the delivery of a single customer view for all stakeholders  MDM architectural styles vary in:  Instantiation of the customer master data — varying from the maintenance of a physical customer profile to a more-virtual, metadata-based indexing structure  The latency of customer master data maintenance — varying from real-time, synchronous, reading and writing of the master data in a transactional context to batch, asynchronous harmonization of the master data across systems  An MDM program potentially encompasses the management of customer, product, asset, person or party, supplier and financial masters.

11. MDM Architecture – Coexistence  Master is Single Version of Truth  Data Quality is Ongoing  Updates occur at Sources or Master  Updates propagated to other Sources Master Source

12. MDM Architecture – Consolidation  Master is Single Version of Truth  Data Quality at Master  Updates occur at Sources  Updates propagated to Master Master Source

13. MDM Architecture – Registry  Multiple Versions of Truth  Data Quality is Ongoing  Updates occur at Sources  Keys and Metadata updated in Registry  Updates propagated to other Sources (Optional) Master Source

14. MDM Architecture – Centralized Master Source  Master is Single Version of Truth  Data Quality at Master  Updates occur at Master  Updates propagated to Sources

15. iWay Solution

16. Data Quality Profiling: Analysis of data to provide insight into the quality of the data and aid in the identification of data quality issues. Parsing and standardization: Decomposition of fields into component parts and formatting of values into consistent layouts based on industry standards, local standards, user- defined business rules and knowledge bases of values and patterns. Generalized "cleansing": Modification of data values to meet domain restrictions, integrity constraints or other business rules that define sufficient data quality for the organization. Matching: Identification, linking or merging related entries within or across sets of data. Monitoring: Deployment of controls to ensure ongoing conformance of data to business rules that define data quality for the organization. Enrichment: Enhancing the value of internally held data by appending related attributes from external sources (for example, consumer demographic attributes or geographic descriptors).

17. iWay Solution CRM iWay Service Manager SFA Content ETL ERP FIN B2B EAI Legacy BI Golden Record Golden Record Index Identify MDM Registry MDM Registry Sync Data Quality Data Quality

18. iWay Solution  Enable online, real-time, near real-time and batch integration  Event based  Push  Pull  Scheduled  Transformation services  Intelligent routing  Correlation of information  Multiple protocol  Transactional update of end systems  Guaranteed delivery of messages

19. SSNFull NamePhone Number AddressCityStateZip Code 205-21-1923John George Malkovich Wachovsky PhD 610-555-14231350 15 th StNewtownPA19073 205-11-1923Dr Charles Becker 6105555423GAPPA17527 221-15-1853Mr. Daniel Deutsch 610.555.6432321 Broad StreetWaynePA19087 205-11-1923Dr C. Becker61055554231173 Kennedy Blvd 17527 305-5`-3423Gregory K Thoben 610-555-1242223 Mallory StKennett SqurPA19348 “Dirty Data” issues Problems : Missing Data Inconsistent Formats Incorrect Data Duplicate Information

20. SSNFull NamePhone Number AddressCityStateZip Code 205-21-1923John George Malkovich Wachovsky PhD 610-555-14231350 15 th StreetNewtownPA19073 205-11-1923Dr Charles Becker 6105555423GAPPA17527 221-15-1853Mr. Daniel Deutsch 610.555.6432321 Broad StWaynePA19087 205-11-1923Dr C. Becker61055554231173 Kennedy Blvd 17527 305-5`-3423Gregory K Thoben 610-555-1242223 Mallory StKennett SqurPA19348 Data Cleansing Correct Address AddressCityStateZipcode 1350 15 th StNewton SquarePA19703 1173 Kennedy BlvdGAPPA17527 3223 Mallory StKennett SquarePA19348

21. SSNFull NamePhone Number AddressCityStateZip Code 205-21-1923John George Malkovich Wachovsky PhD 610-555-14231350 15 th StNewtown SquarePA19073 205-11-1923Dr Charles Becker 6105555423GAPPA17527 221-15-1853Mr. Daniel Deutsch 610.555.6432321 Broad StWaynePA19087 205-11-1923Dr C. Becker61055554231173 Kennedy Blvd GAPPA17527 305-5`-3423Gregory K Thoben 610-555-1242223 Mallory StKennett SquarePA19348 Data Cleansing Phone Number 610-555-1423 610-555-5423 610-555-6432 610-555-1242

22. SSNFull NamePhone Number AddressCityStateZip Code 205-21-1923John George Malkovich Wachovsky PhD 610-555-14231350 15 th StNewtown SquarePA19073 205-11-1923Dr Charles Becker 610-555-5423GAPPA17527 221-15-1853Mr. Daniel Deutsch 610-555-6432321 Broad StWaynePA19087 205-11-1923Dr C. Becker610-555-54231173 Kennedy Blvd GAPPA17527 305-5`-3423Gregory K Thoben 610-555-1242223 Mallory StKennett SquarePA19348 Data Cleansing Reformat Name FirstFirst MiddleInitialLast MiddleLastTitle JohnGeorgeMalkovichWachovskyPhD CharlesBeckerDr DanielDeutschMr. GregoryKThoben

23. Data Cleansing SSNTitleFirst Name F. Middle Int.L.MiddleLast NamePhoneAddrCitySt.Zip 205-21-1923PhdJohnGeorgeMalkovichWachovsky610-555-14231350 15 th StNewtown Square PA19073 205-11-1923Dr.CharlesBecker610-555-5423GAPPA17527 221-15-1853MrDanielDeutsch610-555-6432321 Broad St WaynePA19087 205-11-1923Dr.C.Becker610-555-54231173 Kennedy Blvd GAPPA17527 305-51-3423GregoryKThoben610-555-1242223 Mallory St Kennett Square PA19348 DeDuplicate and Create Golden Record SSNTitleFirst Name F. Middle Int.L.MiddleLast NamePhoneAddrCitySt.Zip 205-21-1923PhdJohnGeorgeMalkovichWachovsky610-555-14231350 15 th StNewtown Square PA19073 205-11-1923Dr.CharlesBecker610-555-54231173 Kennedy Blvd GAPPA17527 221-15-1853MrDanielDeutsch610-555-6432321 Broad StWaynePA19087 305-51-3423GregoryKThoben610-555-1242223 Mallory StKennett Square PA19348

24. Live Demonstration

25. Demonstration Use Case Replacing with iWay Infrastructure: Provides graphical tools to manage process. End to End visibility. Real-time and batch data cleansing and validation