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Using Smart Technologies to Transform Legacy Data into Business Value


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American Banker and Nuxeo webinar. Guest speaker Norman Wren, former Director of Technology & Operations at Santander, and Nuxeo Vice President, Dave Jones, discuss how modernizing legacy data systems using smart technology - like AI, micro-services, and modern content services - can help organizations drive tangible business value and improve the customer experience. They highlight real world examples of practical business applications and solutions.

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Using Smart Technologies to Transform Legacy Data into Business Value

  1. 1. Underwritten by: Using Smart Technologies To Transform Legacy Data into Business Value David Jones & Norman Wren
  2. 2. Underwritten by: Introductions 3 1 David Jones ▪ VP Product Marketing ▪ Nuxeo 2 Norman Wren ▪ Former Technical and Operations Director ▪ Santander
  3. 3. Underwritten by: Digital Transformation – A Reality Check Data is a Ticking Time Bomb Q&A 1 2 3 Agenda
  4. 4. Underwritten by: Introductions 6 David Jones ▪ VP of Product Marketing ▪ Nuxeo ▪ @InstinctiveDave 2 Norman Wren ▪ Former Technical and Operations Director ▪ Santander Digital Transformation A Reality Check
  5. 5. Underwritten by: Digital Transformation in Financial Services Massive Spend Average $42M in 2018 Rising to $45M in 2019 Purpose 66% Customer facing innovations Success? 88% Project delayed, reduced scope, or cancelled 26% Digital Transformation= Insurmountable Task Statistics courtesy of Couchbase
  6. 6. Underwritten by: “Everyone who hears these words of mine, and doesn't do them will be like a foolish man, who built his house on the sand. The rain came down, the floods came, and the winds blew, and beat on that house; and it fell—and great was its fall.” — Matthew 7:24–27
  7. 7. Underwritten by: Building on Sand? Legacy Systems Disconnected Systems Search not find Customer Experience Mobile & Web Apps Performance & Scalability
  8. 8. Underwritten by: #AIIMYour Digital Transformation Begins with Intelligent Information Management Data is a Ticking Time Bomb How to successfully defuse it by leveraging smart technology – Norman Wren
  9. 9. Underwritten by: Why is this important? Customer expectation: Customer in control Unlimited data access Always on 24 x 7 Real time Added value services Regulation : Customer rights Data portability Open access to third parties Remediation of historic practices Internal driver: Exploit data assets
  10. 10. Underwritten by: Legacy Data Challenges • Fragmented data ; not real time; internal view; unstructured data; access limited • Multiple formats; limited documentation; knowledge gap • Integrity within applications not across; degradation over time • Security and data leakage • Obsolescence • Compliance with regulation • Cost of Change; time to market ; consolidation of data stores. • Architecture and technology compatibility • BAU Running costs • No scalability; access limitations; poor schema design Access Data Quality and Integrity Risk Cost Performance
  11. 11. Underwritten by: Value: 3 Basic Requirements ➢ Find Data ➢ Document attributes and meaning ➢ Understand usage and context ➢ Define architecture ➢ Set usage, access and security rules ➢ Build governance and ownership ➢ Organize around common business purposes ➢ Make accessible through common access layer ➢ Use metadata to organize and add value ➢ Build new capabilities – data driven Understand the Data Manage the Data Exploit the Data 3 1 2
  12. 12. Underwritten by: Considerations Archaeology: Find and document data and how used Architecture: Define data architecture and principles Data ECO system: Distributed data Define data usage: Update; query; analytics Common Layer: To bridge technologies Scaleability: Cloud processing; distributed data Ownership: Governance and accountability
  13. 13. Underwritten by: Key Points “Data as an Asset” needs: • Clear ownership and accountability • Knowledge and documentation meta data • Clear understanding of usage and value • Data architects and engineers • Architectural readiness • Capability • Data strategy
  14. 14. Underwritten by: Stick or Twist? ➢ Obsolescence ➢ Security ➢ Maintenance ➢ Cost ➢ Risk ➢ Cost ➢ Risk ➢ Data Quality ➢ Integrity ➢ Business case ➢ Less Risk ➢ Unlock assets ➢ Bridge old and new ➢ Create data eco system for the future Do Nothing Big Bang Migration Co-Existence/ Common Layer
  15. 15. Underwritten by: Summary • Data knowledge and documentation fundamental • Hard work and time consuming • Clear target architecture addressing data • Technology stack and data usage • Common layer to separate data from business processing • Avoid migration if possible • Avoid pitfall of access in situ • Define common business purposes • Build road map • Balance value, cost and risk • Invest in capability
  16. 16. Underwritten by: Thank You Twitter: @instinctivedave Email: