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Iron Architect 2007

Matthew Roche Chief Software Architect Integral Thought & Memory matthew@itandm.com. Iron Architect 2007. Lodging Problem Summary. Enhance TechEd attendee experience through: Attendee lodging clustering Targeted events Location-driven social networking Inputs:

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Iron Architect 2007

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  1. Matthew Roche Chief Software Architect Integral Thought & Memory matthew@itandm.com Iron Architect 2007

  2. Lodging Problem Summary • Enhance TechEd attendee experience through: • Attendee lodging clustering • Targeted events • Location-driven social networking • Inputs: • Attendee profiles (role, vertical, tech/product focus, other • Hotel profiles • Previous years’ attendance data • “Seed” recommendations • Outputs • Recommendations for attendee lodging selection • Schedule for ATE and BOF sessions • Recommendations for ad hoc attendee networking opportunities

  3. Project Overview • Risks • 36 hotels - Disparate hotel systems • Work with select partner hotels early • Ensure partners are representative • Attendees unwilling to provide profile details • Effectively communicate benefit • Introduce detailed user profile at earlier conferences (Mix, MEDC, TechReady, etc.) • Failure to achieve critical mass • “Seed” hotels based on previous years or arbitrary selection • Introduce flexible rebalancing of attendee reservations • Process • Iterative, risk driven model • Communication plan for project team members and

  4. Solution Overview • Reuse: Wherever possible, components of existing registration system will be reused with minimal modification • ASPX Attendee UI – add new fields and pages for profile • Hotel reservation system integration – add rebooking/rebalancing capabilities • Extension: Where necessary, new components will be introduced to add required functionality • Event scheduling components – integrate with EventPoint/CommNet • Integrate with email/text message notification gateway for • Core Logic: • Service Oriented Architecture with contracts and policies defined for cross-system communication • SQL Server Analysis Services Data Mining for clustering, grouping, categorization and predictive analysis to cluster attendees based on profile characteristics

  5. High-Level Architecture • Service Oriented Architecture – Well-defined boundaries and contracts • Core service interacts with existing event and lodging systems • Core functionality provided by SSAS data mining models • Rich attendee profiles with well-defined criteria and ad hoc tagging capabilities for rich self-description • “Rebook me” functionality so attendees can opt in to be automatically rebooked to another hotel within specific criteria if future attendee registrations change early cluster predictions • Integrate with text message gateway for change notification

  6. High-Level Architectural Diagram

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