Crossing the Mashup Chasm Requirements for Enterprise Mashups March 20th 2008 Justo Hidalgo VP Technology [email_address] Juan Lozano Principal Software Engineer [email_address] ashupCamp.com

What am I looking for in this discussion?

Agenda Background Web mashups and Enterprise Data Mashups Requirement areas Further thoughts

Background

Web mashups and Enterprise Data Mashups

Requirement areas

Further thoughts

Background Justo N. Hidalgo VP Technology Denodo Technologies, Palo Alto Ph.D. Computer Science in Query Optimization in Mediators of Web Sources Interest in how Enterprise Data Mashups evolve. Juan Lozano Principal Software Engineer Denodo Technologies, Palo Alto Our “web wrapper” guru  Product (Denodo Platform 4.1) Enterprise Data Mashups & Web Automation Data Integration of Structured, Web and Unstructured Information 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

Justo N. Hidalgo

VP Technology Denodo Technologies, Palo Alto

Ph.D. Computer Science in Query Optimization in Mediators of Web Sources

Interest in how Enterprise Data Mashups evolve.

Juan Lozano

Principal Software Engineer Denodo Technologies, Palo Alto

Our “web wrapper” guru 

Product (Denodo Platform 4.1)

Enterprise Data Mashups & Web Automation

Data Integration of Structured, Web and Unstructured Information

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

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

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

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 ?

Customer Uses of Enterprise Data Mashups 1. Aggregate Data 3. Exchange Data Enterprise Suppliers Customers 2. Enrich Data Apps Data Services

Requirement Areas: Mashups for Business Users / For Power Users and IT User experience Heterogeneous granularity for different levels

User experience

Heterogeneous granularity for different levels

Requirement Areas: Enterprise-class features… Security LDAP access, user and role permission levels, But also: Secure VPNs, secure communications, encryption 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

Security

LDAP access, user and role permission levels,

But also: Secure VPNs, secure communications, encryption

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

Requirement Areas: …Enterprise-class features Data Transformations Biopharma example: contextual summaries, patterns and regular expressions LinkedForce example: textual similarity Maintenance Sources change… specially Web Sites!!! Data Management… don´t get me started  What are the boundaries between mashups and MDM, Data Quality tools?

Data Transformations

Biopharma example: contextual summaries, patterns and regular expressions

LinkedForce example: textual similarity

Maintenance

Sources change… specially Web Sites!!!

Data Management… don´t get me started 

What are the boundaries between mashups and MDM, Data Quality tools?

Requirement Areas: Ecosystem SOURCES: WEB, PACKAGED APPS, MAINFRAME, … DATA QUALITY, METADATA, STANDARDS REST, SOAP, MQSERIES, ESB, JDBC, JSR-168

Further thoughts “ Semantic mashups”: Automatic schema matching Automatic Browsing and Information Structuring … “ Real Time” mashups I mean… HARD REAL TIME.

“ Semantic mashups”:

Automatic schema matching

Automatic Browsing and Information Structuring

…

“ Real Time” mashups

I mean… HARD REAL TIME.

Thank You! Justo Hidalgo, VP Technology Email [email_address] Juan Lozano, Principal Software Engineer Email [email_address] http://www.denodo.com