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Gene Leganza Vice President Forrester Research


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Gene Leganza Vice President Forrester Research

  1. 1. July 20, 2004. Call in at 12:55 p.m. Eastern Time Gene Leganza Vice President Forrester Research ForrTel: Creating The Information Architecture Function
  2. 2. Agenda <ul><li>Information architecture: A definition </li></ul><ul><li>A description of the problem: Drivers for information architecture </li></ul><ul><li>Benefits, risks, and obstacles of an information architecture program </li></ul><ul><li>Creating the road map to a successful program </li></ul><ul><li>Achieving the strategic through tactical steps </li></ul>
  3. 3. Definition <ul><li>Information architecture structures data and data relationships to facilitate analyses that feed business strategy and optimization decisions. It also serves as a link between business architecture and application architecture, providing a foundation for application design and delivery. It is a high-level construct for organizing all business uses of information in an enterprise. </li></ul>
  4. 4. Enterprise architecture
  5. 5. Drivers for information architecture <ul><li>Increasing data sources </li></ul><ul><li>Increasing need for integration </li></ul><ul><li>Data stored in apps is redundant and inconsistent </li></ul><ul><li>Data is isolated </li></ul><ul><li>Informal data extractions become business critical </li></ul><ul><li>No data supports the enterprise view </li></ul><ul><li>Increasing importance of unstructured data </li></ul><ul><li>Increased regulatory scrutiny </li></ul>
  6. 6. Data integration: Major architecture driver Source: March 31, 2004, Best Practices “Successful Data Integration Requires Architecture”
  7. 7. Benefits of introducing information architecture <ul><li>Enterprise-wide metadata repository creates central source of truth </li></ul><ul><li>Systemic data quality </li></ul><ul><li>Systemic processes to ensure security </li></ul><ul><li>Standard processes for data access </li></ul><ul><li>Architected data integration </li></ul><ul><li>Best practices data management </li></ul><ul><li>Well-bounded environments </li></ul><ul><li>Well-defined data storage requirements </li></ul>
  8. 8. Distributed ETL Architecture
  9. 9. Risks and obstacles <ul><li>It is a long-term program </li></ul><ul><li>Lack of continuity destroys incremental benefits </li></ul><ul><li>Resource commitment is critical </li></ul><ul><li>Is a cross-divisional effort </li></ul><ul><li>Data ownership is a common political obstacle </li></ul><ul><li>Terminology and conceptual issues obscure the goal </li></ul>
  10. 10. Creating the road map Business case and management buy-in Context: EA program Create a comprehensive communication program Plan short-term deliverables Include business & IT stakeholders Implement a pilot or prototype
  11. 11. Data warehouse reference architecture
  12. 12. Recommendations: Achieving the strategic through tactical steps <ul><li>Begin with a clear understanding of the current state </li></ul><ul><li>Define the enterprise wide target state at a high level </li></ul><ul><li>Research and select key technology components </li></ul><ul><li>Select low-risk, medium-impact project for pilot implementation </li></ul><ul><li>Evaluate pilot exhaustively for lessons learned </li></ul><ul><li>Broaden program based on success </li></ul>
  13. 13. Thank you Gene Leganza [email_address] Entire contents © 2004 Forrester Research, Inc. All rights reserved.