When Business Met IT Can Two Friends Mashup Together and still Love each other in the Morning? Introduction to Enterprise Data Mashups September 4 th 2008 Justo Hidalgo VP Product Management and Consulting [email_address] Copyright held by the film company or the artist. Claimed as fair use regardless.

Mashups are Crossing the Chasm

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

Background

Enterprise Mashups

Web mashups and Enterprise Data Mashups

Some real-world examples

Research Areas

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 4.5 - 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

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 4.5 - 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

Moi VP Product Management and Consulting, Denodo Technologies, Madrid Two hats: Product Management, and Sales Engineering and Consulting Ph.D. Computer Science, Query Optimization in Mediators of Web Sources Working in Enterprise Data Integration since 2000 jhidalgo at domain denodo dot com http://justohidalgo.blogspot.com This presentation will be available at: http://www.slideshare.net/justohidalgo/

VP Product Management and Consulting, Denodo Technologies, Madrid

Two hats: Product Management, and Sales Engineering and Consulting

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

Working in Enterprise Data Integration since 2000

jhidalgo at domain denodo dot com

http://justohidalgo.blogspot.com

This presentation will be available at:

http://www.slideshare.net/justohidalgo/

Enterprise Mashups

Needs 1. Aggregate Data 3. Exchange Data Enterprise Suppliers Customers 2. Enrich Data Apps Data Services

Enterprise Mashup Architecture, according to the Analysts

Denodo Combines the “Innovation” of Web Mashups … “ These technologies are more basic, with ease of use as the primary design criteria” “ These technologies will, for the most part, not satisfy a broad robust enterprise need but may serve as point tools to enhance the overall strength of the enterprise mashup architecture.” - Gartner

With “Enterprise-Class” Features and Quality of Service “ Denodo Technologies - Cool Vendor 2007” “ Denodo offers mashup capabilities that are very strong in accessing and processing information from a variety of internal and external sources for delivery as a "mashable" feed.” Information integration is their core competency. ” - Gartner

Enterprise Data Mashup Architecture, according to us 

A little bit more detail

Web and Data Mashups

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 ?

Requirement Areas

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

User experience

Pipes&Filters, Data Federation

Heterogeneous granularity for different levels

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

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

… 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? Packaged Apps SAP, Siebel, Oracle Apps, Greenscreens, …

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?

Packaged Apps

SAP, Siebel, Oracle Apps, Greenscreens, …

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

Maintenance

Sources change… specially Web Sites!!!

Automatic Extraction

Schema matching

Automatic wrapper induction

Automatic Browsing

Taxonomy-based path recognition

Form updates

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

Architecture

A new Mashup Reference Architecture

Web Data Extraction

Automatic Web Data Extraction

Automatic Web Maintenance

Extraction Templates

Enterprise-class

Query Optimization Techniques

1. Data Aggregation

Holistic View of Customer - Solution Architecture Clientes Ventas Siebel Singl.eView Street directory Remedy Enterprise Data Mashups Vitria Product Catalog TV Scheduling Excel, CSV, .. Network Services Provision CRM, … Customers CC Customer Support Service Portal Internet Distributors Distributors Portal Marketing Dpt. Sales Dpt. After-Sales Dpt. Registry Debt Control Competitor Price Comparison

2. Data Enrichment

Competitive Price Comparison … Denodo Web Automation & Extraction Can Access Structured Data Hiding Behind Web Interfaces Access Competitors Website for up-to-date product information Automatic web navigation – use zip code to find available products in your area Extract product information from websites into internal database Websites contain product information Internal Database

Competitive Data Mashup for Sales Automation Leads Process Automated by Denodo Competitors Physician Registry Industry Organizations Leads Sorted by Territory CRM System

Workflow - Measure Lead Quality Combined physician list CRM Contact History 3. Workflow Publish Process Extracted Name Contact Name Pamel, Gregory J. Pamel, Greg J. Belmont, Sandra Belmont, Sandy Fox, Martin L. Fox, Martin Qualifications & Academic Listings Names Quality of Lead – based on: On Competitor Site (1 pt) Prominence (1 pt) matches 2 or more keywords Location - near rep (1 pt) In CRM System (1 pt) Lead Quality 3,4 pts - High 2 pts – Med 1 pt - Low Name Association to Keywords Keyword Taxonomy Filters LASIK Excimer laser Keratomileusis Microkeratome Bladeless PRK - Photorefractive Keratectomy Refractive Surgery Index of all keywords associated with names

Quality of Lead – based on:

On Competitor Site (1 pt)

Prominence (1 pt)

matches 2 or more keywords

Location - near rep (1 pt)

In CRM System (1 pt)

Publish - Map New Leads based on Quality Score Visual Competitive Sales Guide Hi Score Med Score Low Score Key

3. Data Exchange

Q&A Justo Hidalgo VP Technology [email_address]