iway Omni-Gen Rethinking your approach to MDM with iway Omni-Gen James Cotton iway Solution Director

Transcription

1 iway Omni-Gen Rethinking your approach to MDM with iway Omni-Gen James Cotton iway Solution Director 1

2 Intelligence Portal Embedded InfoApps Hot Social Bad Feedback Predictive Analytics Sentiment and Word Analytics Search Location Analytics Mobile Write-Back Data Discovery Reporting Dashboards Casting and Archiving Active Technologies High-Performance Data Store Integrity Data Quality Master Data Management Data Governance Integration Batch ETL Real-Time ESB Legacy Systems Applications Relational/Cubes Big Data Columnar/In Memory Unstructured Social Media Web Services Trading Partners

3 What is MDM

4 Types of data in an organisation Unstructured Transactional Metadata Hierarchical Master

5 Understanding Master Data Bob Smith buys a widget (SKU #A1234) and ships it to his home address The master data elements are the nouns and are people, things, and places The transactional data elements are verbs that describe what happens to those people, places, and things. CRM Marketing ERP WMS Financial

6 iway Omni-Gen The Basics: Understanding Master Data Name: Bob Smith Tel: DOB: 23/10/71 Gender: M Name: Bob Smith Tel: DOB: Gender: M Name: Bob Smith Tel: DOB: Gender: Male Name: B Smith Tel: DOB: 23/10/71 Gender: M Name: B Smith Tel: (0) DOB: 23-Oct-71 Gender: M Name: Bob Smith Tel: DOB: 23/10/71 Gender: Name: Smiht, Bob Tel: (01283)56982 DOB: 23/10/1971 Gender: CRM Marketing ERP WMS Financial

7 How many people are here? Source data Name Gender SIN Birth Date Address Dr. John Smith M /12/1978 Ringmore rise,22 se23 3de Smiht W. John Male SE23 3DE, 22 John William Smith SIN Arnoldstreet, Bolton, NE91 98D Dr. J.W. Smith M /16/78 John Smith cat ave, Pembroke Dock, SA72 6Y Smith John Cataline Avenue 3, Pembroke, SA72 6YB John Smiht Jane Watson cat ave, Pembroke Dock, SA72 6Y Watson Jane F Catalina Avenue, Pembroke Dock Jane Smith 0 SIN J. Smith

8 How many people are here? Cleansed data First Last G SIN Birth Date Address John Smith M 16/12/ Ringmore Rise, London, SE23 3DE John Smiht M /12/ Ringmore Rise, London, SE23 3DE John Smith M Arnold Street, Boldon Colliery, Bolton, NE35 9BD Smith M 16/11/1978 John Smith M /11/ Catalina Avenue, Pembroke Dock, SA72 6YB John Smith M 16/11/ Catalina Avenue, Pembroke Dock, SA72 6YB John Smiht M /11/1978 Jane Watson F Catalina Avenue, Pembroke Dock, SA72 6YB Jane Watson F /01/ Catalina Avenue, Pembroke Dock, SA72 6YB Jane Smith F /01/1982 J. Smith

9 Match Cleansed data First Last G SIN Birth Date Address John Smith M 16/12/ Ringmore Rise, London, SE23 3DE John Smiht M /12/ Ringmore Rise, London, SE23 3DE John Smith M Arnold Street, Boldon Colliery, Bolton, NE35 9BD Smith M 16/11/1978 John Smith M /11/ Catalina Avenue, Pembroke Dock, SA72 6YB John Smith M 16/11/ Catalina Avenue, Pembroke Dock, SA72 6YB John Smiht M /11/1978 Jane Watson F Catalina Avenue, Pembroke Dock, SA72 6YB Jane Watson F /01/ Catalina Avenue, Pembroke Dock, SA72 6YB Jane Smith F /01/1982 J. Smith

10 Merge Cleansed data First Last G SIN Birth Date Address John Smith M 16/12/ Ringmore Rise, London, SE23 3DE John Smiht M /12/ Ringmore Rise, London, SE23 3DE John Smith M Arnold Street, Boldon Colliery, Bolton, NE35 9BD Golden record First Last G SIN Birth Date Address The The newest most permanent frequent address

11 Types of MDM Analytical vs. Operational

12 iway Omni-Gen Analytical MDM Analytical data is used to support a company's decision making Analytical MDM centres on assuring single view of master data in the downstream data warehouse used most often to supply the data for a business intelligence (BI) solution for historical and predictive analysis Any data cleansing done inside an Analytical MDM solution is invisible to the transactional applications

13 iway Omni-Gen Operational MDM Operational data is the lifeblood of an organisation Operational MDM centres on assuring single view of master data in the core systems used by business users Sales, service, order management, manufacturing, purchasing, billing, accounts receivable, accounts payable, payroll, etc. Rely heavily on integration technologies to keep systems in sync

14 Use Case Analytical MDM AkzoNobel HR 14

15 AkzoNobel HR Analytical MDM World largest chemical company 52 HR applications across the globe Part of an SAP integration project (OneHR) Decentralized Data Governance No idea how many employees they had

16 Use Case Operational MDM Informa 16

17 Informa Operational MDM Global marketing company combining over 100 databases Ongoing data quality as new data is constantly being added Validating address data Matching and merging data across all data sources Updating the individual applications with the best data Reduced total # records by 30%

18 Approach to MDM

19 MDM Typical approach MDM App (End State) MDM hub Data warehouse Partner interface Quality process Operational systems BI/analytics app

20 MDM The real work behind MDM MDM Projects Transformational at the business level Technically complex Dependent on solid architecture Project Components Integration Quality and standardization Mastering Consumption artifact generation Historical data management Testing Issue remediation Staffing requirements Integration expertise Mastering expertise Business process transformation experience Testing and quality assurance

21 iway Omni-Gen Agile approach MDM App (End State) MDM hub Data warehouse Partner interface Quality process Operational systems BI/analytics app

22 Data Management Lifecycle Cloud-based systems Legacy assets ERP applications Business partners Cloud-based systems Downstream applications Data warehouses Business partners

23 Demonstration Omni Designer 23

24 Demonstration Omni Governance Console 24

25 Omni-Gen editions

26 Information Management Value Index Multipurpose Real-time Event-Driven Multisystem DQ firewall Remediation Multidomain Single 360 view

27 iway Omni-Gen Omni-Gen Master Data Management Edition Data Quality Edition Data Integration Edition Profiling Integration Cleansing Mastering

28 iway Omni-Gen Understanding the Content and Scope of the Data Data Quality Repository for History Out of the Box Reports Trending Analysis Legacy Application Applications Standard and Custom Statistics Key Analysis, Masking, Dependency and more Big Data Trading Partners Data Profile Integrate Cleanse Master

29 iway Omni-Gen Integration as a Process Unique and Powerful Enterprise Integration Service Bus Platform and Batch Movement Real time and Batch, Event-based Legacy Application Applications Compose, Orchestrate and Automate Complex Integration Processes Graphical Service Creation Configuration Oriented Big Data Trading Partners Data Pre-Built Integration components Data, Apps, Format, etc. Native EDI, HIPAA, HL7 capabilities Integration Edition Profile Integrate Cleanse Master

30 iway Omni-Gen Quality as a Process Reusable Profiling Rules with no coding or recoding Enrich, Clean, and Enhance Data Legacy Application Applications Real Time Data Quality Firewall and Analysis for Services and BI Match and Merge across Multiple Data Sets Big Data Trading Partners Data Remediate Suspect or Incorrect Data Data Quality Edition Integration Edition Profile Integrate Cleanse Master

31 iway Omni-Gen Configure Data Quality components Full Data Quality Solution Data Cleansing and Standardization Stewardship Portal for Remediation Knowledge Bases Names Address Custom Repositories Matching / Merging Probabilistic and Deterministic Levenshtein distance John Smith y =f x Id column for Names Alter Format Remove titles Strip Titles Parse Names Guess Name Surname Prepare out values Column Assigner Remove columns Alter Format

32 iway Omni-Gen Mastering as a Process Mastering is more than a Repository, it is a Process Works seamlessly with Quality Services, Integration Layer, Data Repositories, and Governance applications Legacy Application Applications Model Driven assembly of Mastering Applications Definition of Entry and Exit points Orchestration of all aspects of the Mastering Process including workflows, Data Quality, Governance Big Data Trading Partners Data Master Data Management Edition Data Quality Edition Integration Edition Profile Integrate Cleanse Master

33 Thank You