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

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