When Business Met IT. Can Two Friends Mashup Together and still Love each other in the Morning? Presentation given at UC Berkeley, hosted by Prof. Raymond Yee. I discuss the challenges faced by Enterprise Data Integration and Mashups to find a place in the core data infrastructure

1. When Business Met IT Can Two Friends Mashup Together and still Love each other in the Morning? Introduction to Enterprise Data Mashups April 28th 2008 Justo Hidalgo VP Technology [email_address] Copyright held by the film company or the artist. Claimed as fair use regardless.

2. Mashups are Crossing the Chasm

3. Agenda Background Enterprise Mashups Web mashups and Enterprise Data Mashups Some real-world examples Research Areas

4. Denodo Company Founded 1999, Europe 2005, NA HQ in 2006, APAC SIs 2007 Profitable in Europe; Venture-backed global expansion Operations Americas & EMEA; VARs in Asia 75+ Customers – Telco, Fin Svcs, Energy, Health, Govt / Defense Expanding Partners - Focused ISVs, SaaS, SI/VARs Product (Denodo Platform 4.1 - Enterprise Hardened) Enterprise Data Mashups & Web Automation Data Integration of Structured, Web and Unstructured Information Fast, Agile Deployments in under 30 days Technology Focus: Data Integration, Web 2.0 & Mashup Enabler Targeted Solutions: Intelligence, Single View, Web Automation Tenths of projects in the last 12 months to learn from Q2 2008: Denodo Platform 4.5

5. Justo VP Technology Denodo Technologies, Palo Alto Responsible for Product Management and Product Development Ph.D. Computer Science, Query Optimization in Mediators of Web Sources Working in Enterprise Data Integration since 2000 jhidalgo at domain denodo dot com If you read spanish: http://justohidalgo.blogspot.com This presentation is available at: http://www.slideshare.net/justohidalgo/

6. Enterprise Mashups

7. Enterprise Mashup Architecture, according to the Analysts

8. Enterprise Data Mashup Architecture, according to us 

9. A little bit more detail

10. Web and Data Mashups

11. Web Mashups vs. Data Mashups Web Mashups Visual centric Data relationships are simple End-user driven enabled by APIs / tools No QoS guarantees – as is Simple Web security Data Mashups Data & Information centric Deep transformations & semantic relationships Interact with Enterprise ecosystem Business analyst driven w/ user control options Enterprise QoS- Query Optimization, Reliable, Failover, etc. Policy-based security ENTERPRISE ECOSYSTEM Enterprise Infrastructure / Web Platform Enterprise & Web Applications RIA, Social Software, GUI, Portals

12. Mutual Benefits Web Mashups Data Mashups Enterprise Data Integration BPM ESB EAI ETL Data Warehouses Enterprise Infrastructure / Web Platform Enterprise & Web Applications RIA, Social Software, GUI, Portals ENTERPRISE ECOSYSTEM WEB MASHUPS DATA MASHUPS User experience / global access Enterprise-class features ?

13. What, Enterprise Mashups are not for cool things? 1. Aggregate Data 3. Exchange Data Enterprise Suppliers Customers 2. Enrich Data Apps Data Services

14. Requirement Areas

15. Mashups for Business Users / For Power Users and IT User experience Pipes&Filters, Data Federation Heterogeneous granularity for different levels

16. Enterprise-class features… Security LDAP access, user and role permission levels, … But also: Secure VPNs, secure communications, encryption, SSO EXAMPLE: Financial Aggregation HA/Scalability Load balancing Federated and distributed architectures EXAMPLE: TELE-2/Vodafone Call Center Performance Asynchronous access Parallelism Execution Plan Optimization techniques

17. … Enterprise-class features Data Transformations Biopharma example: contextual summaries, patterns and regular expressions LinkedForce example: textual similarity Data Management… don´t get me started  What are the boundaries between mashups and MDM, Data Quality tools? Standards and Integration JSR-168, JMX, JMX, JDBC, ODBC, WS-*, microformats, … don´t you love standardization bodies?

18. Automatic Browsing and Structure Maintenance Sources change… specially Web Sites!!! Automatic Extraction Schema matching Automatic wrapper induction Automatic Browsing Taxonomy-based path recognition Form updates

19. Research Architecture A new Mashup Reference Architecture Web Data Extraction Automatic Web Data Extraction Automatic Web Maintenance Extraction Templates Enterprise-class Query Optimization Techniques

20. Q&A Justo Hidalgo VP Technology [email_address]