Wouldn’t it be nice if…? An Introduction to Enterprise Data Mashups at the School of Information, UC Berkeley Feb 11th, 20...
…  I could use information for all these sources without going crazy? CRM (MySQL) Billing System (Web Service - Rest) Inci...
Extracción de Datos Web Estructuración y Navegación Automática.  Estado del Arte y Propuesta Investigadora de Denodo <ul><...
…  I could do it in batch mode, where required?
…  I could react rapidly to changes?
…  I could do this without having to code it all?
…  , finally, I could do this for actual ENTERPRISE PROBLEMS AND NEEDS???
Mashups are Crossing the Chasm
Agenda <ul><li>Background </li></ul><ul><li>Enterprise Mashups </li></ul><ul><li>Web mashups and Enterprise Data Mashups <...
Denodo <ul><li>Company   </li></ul><ul><li>Founded 1999, Europe 2005, NA HQ in 2006, APAC SIs 2007, East, Midwest 2009 </l...
 
Justo <ul><li>VP Product Management and Consulting, Denodo Technologies </li></ul><ul><ul><li>Responsible for Product Mana...
Enterprise Mashups
Enterprise Mashup Architecture, according to the Analysts
 
A little bit more detail
What, Enterprise Mashups are not for cool things? 1. Aggregate Data 3. Exchange Data Enterprise Suppliers Customers 2. Enr...
Web and Data Mashups
Web Mashups vs. Data Mashups <ul><li>Web Mashups </li></ul><ul><li>Visual centric </li></ul><ul><li>Data relationships are...
Mutual Benefits Web Mashups Data Mashups Enterprise Data Integration  BPM ESB EAI ETL Data Warehouses Enterprise Infrastru...
Enterprise Areas
Mashups for Business Users / For Power Users and IT <ul><li>User experience </li></ul><ul><ul><li>Pipes&Filters, Data Fede...
Enterprise-class features… <ul><li>Security </li></ul><ul><ul><li>LDAP access, user and role permission levels, … </li></u...
… Enterprise-class features <ul><li>Data Transformations </li></ul><ul><ul><li>Textual similarity, contextual summaries, p...
Automatic Browsing and Structure   <ul><li>Maintenance </li></ul><ul><ul><li>Sources change… specially Web Sites!!! </li><...
Research <ul><li>Architecture </li></ul><ul><ul><li>A new Mashup Reference Architecture </li></ul></ul><ul><li>Web Data Ex...
A few references <ul><li>Information Structuring </li></ul><ul><ul><li>Manuel Álvarez, Alberto Pan, Juan Raposo, Fernando ...
Q&A Justo Hidalgo VP Product Management and Consulting [email_address]
<ul><li>All images shown that are not property of Denodo come from the search engine search.creativecommons.org, that sear...
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Wouldn't it be nice if... an introduction to Enterprise Data Mashups

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Wouldn't it be nice if... an introduction to Enterprise Data Mashups
by Justo Hidalgo (Denodo Technologies)

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  • Wouldn't it be nice if... an introduction to Enterprise Data Mashups

    1. 1. Wouldn’t it be nice if…? An Introduction to Enterprise Data Mashups at the School of Information, UC Berkeley Feb 11th, 2008 Justo N. Hidalgo VP Product Management and Consulting Denodo
    2. 2. … I could use information for all these sources without going crazy? CRM (MySQL) Billing System (Web Service - Rest) Incidences System (Web Application) Inventory System (MS SQL Server) Product Catalog (Web Service -SOAP) Knowledge Base (Internet) Product Data (CSV) Log files (.txt/.log files)
    3. 3. Extracción de Datos Web Estructuración y Navegación Automática. Estado del Arte y Propuesta Investigadora de Denodo <ul><li>Justo N. Hidalgo, VP Product Management and Consulting </li></ul><ul><li>21 de Enero de 2009 </li></ul>… I could do it in real time, where required? CRM (MySQL) Billing System (Web Service - Rest) Incidences System (Web Application) Inventory System (MS SQL Server) Product Catalog (Web Service -SOAP) Knowledge Base (Internet) Product Data (CSV) Log files (.txt/.log files)
    4. 4. … I could do it in batch mode, where required?
    5. 5. … I could react rapidly to changes?
    6. 6. … I could do this without having to code it all?
    7. 7. … , finally, I could do this for actual ENTERPRISE PROBLEMS AND NEEDS???
    8. 8. Mashups are Crossing the Chasm
    9. 9. Agenda <ul><li>Background </li></ul><ul><li>Enterprise Mashups </li></ul><ul><li>Web mashups and Enterprise Data Mashups </li></ul><ul><li>Some real-world examples </li></ul><ul><li>Research Areas </li></ul>
    10. 10. Denodo <ul><li>Company </li></ul><ul><li>Founded 1999, Europe 2005, NA HQ in 2006, APAC SIs 2007, East, Midwest 2009 </li></ul><ul><li>Profitable in Europe; Venture-backed global expansion </li></ul><ul><li>Operations </li></ul><ul><li>Americas & EMEA; VARs in Asia </li></ul><ul><li>90+ Customers – Telco, Fin Svcs, Energy, Health, Govt / Defense </li></ul><ul><li>Expanding Partners - Focused ISVs, SaaS, SI/VARs </li></ul><ul><li>Product (Denodo Platform 4.5 - Enterprise Hardened) </li></ul><ul><li>Enterprise Data Mashups & Web Automation </li></ul><ul><ul><li>Data Integration of Structured, Web and Unstructured Information </li></ul></ul><ul><ul><li>Fast, Agile Deployments in under 30 days </li></ul></ul><ul><li>Technology Focus: Data Integration, Web 2.0 & Mashup Enabler </li></ul><ul><li>Targeted Solutions: Intelligence, Single View, Web Automation </li></ul><ul><li>Tenths of projects in the last 18 months to learn from </li></ul><ul><li>Q4 2009: Denodo Platform 5.0 </li></ul>
    11. 12. Justo <ul><li>VP Product Management and Consulting, Denodo Technologies </li></ul><ul><ul><li>Responsible for Product Management and Sales Engineering </li></ul></ul><ul><li>Ph.D. Computer Science, Query Optimization in Mediators of Web Sources </li></ul><ul><li>Working in Enterprise Data Integration and Web Process Automation since 2000 </li></ul><ul><li>jhidalgo at domain denodo dot com </li></ul><ul><li>If you read spanish: http://justohidalgo.blogspot.com </li></ul><ul><li>This presentation is available at: </li></ul><ul><ul><li>http://www.slideshare.net/justohidalgo/ </li></ul></ul>
    12. 13. Enterprise Mashups
    13. 14. Enterprise Mashup Architecture, according to the Analysts
    14. 16. A little bit more detail
    15. 17. What, Enterprise Mashups are not for cool things? 1. Aggregate Data 3. Exchange Data Enterprise Suppliers Customers 2. Enrich Data Apps Data Services
    16. 18. Web and Data Mashups
    17. 19. Web Mashups vs. Data Mashups <ul><li>Web Mashups </li></ul><ul><li>Visual centric </li></ul><ul><li>Data relationships are simple </li></ul><ul><li>End-user driven enabled by APIs / tools </li></ul><ul><li>No QoS guarantees – as is </li></ul><ul><li>Simple Web security </li></ul><ul><li>Data Mashups </li></ul><ul><li>Data & Information centric </li></ul><ul><li>Deep transformations & semantic relationships </li></ul><ul><li>Interact with Enterprise ecosystem </li></ul><ul><li>Business analyst driven w/ user control options </li></ul><ul><li>Enterprise QoS- Query Optimization, Reliable, Failover, etc. </li></ul><ul><li>Policy-based security </li></ul>ENTERPRISE ECOSYSTEM Enterprise Infrastructure / Web Platform Enterprise & Web Applications RIA, Social Software, GUI, Portals
    18. 20. 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 ?
    19. 21. Enterprise Areas
    20. 22. Mashups for Business Users / For Power Users and IT <ul><li>User experience </li></ul><ul><ul><li>Pipes&Filters, Data Federation </li></ul></ul><ul><li>Heterogeneous granularity for different levels </li></ul>
    21. 23. Enterprise-class features… <ul><li>Security </li></ul><ul><ul><li>LDAP access, user and role permission levels, … </li></ul></ul><ul><ul><li>But also: Secure VPNs, secure communications, encryption, SSO </li></ul></ul><ul><li>HA/Scalability </li></ul><ul><ul><li>Load balancing </li></ul></ul><ul><ul><li>Federated and distributed architectures </li></ul></ul><ul><li>Performance </li></ul><ul><ul><li>Asynchronous access </li></ul></ul><ul><ul><li>Parallelism </li></ul></ul><ul><ul><li>Execution Plan Optimization techniques </li></ul></ul>
    22. 24. … Enterprise-class features <ul><li>Data Transformations </li></ul><ul><ul><li>Textual similarity, contextual summaries, patterns and regular expressions </li></ul></ul><ul><li>Data Management… don´t get me started  </li></ul><ul><ul><li>What are the boundaries between mashups and MDM, Data Quality tools? </li></ul></ul><ul><li>Standards and Integration </li></ul><ul><ul><li>JSR-168, JMX, JMX, JDBC, ODBC, WS-*, microformats, … don´t you love standardization bodies? </li></ul></ul>
    23. 25. Automatic Browsing and Structure <ul><li>Maintenance </li></ul><ul><ul><li>Sources change… specially Web Sites!!! </li></ul></ul><ul><li>Automatic Extraction </li></ul><ul><ul><li>Schema matching </li></ul></ul><ul><ul><li>Automatic wrapper induction </li></ul></ul><ul><li>Automatic Browsing </li></ul><ul><ul><li>Taxonomy-based path recognition </li></ul></ul><ul><ul><li>Form updates </li></ul></ul>
    24. 26. Research <ul><li>Architecture </li></ul><ul><ul><li>A new Mashup Reference Architecture </li></ul></ul><ul><li>Web Data Extraction </li></ul><ul><ul><li>Automatic Web Data Extraction </li></ul></ul><ul><ul><li>Automatic Web Maintenance </li></ul></ul><ul><ul><li>Extraction Templates </li></ul></ul><ul><li>Enterprise-class </li></ul><ul><ul><li>Query Optimization Techniques </li></ul></ul>
    25. 27. A few references <ul><li>Information Structuring </li></ul><ul><ul><li>Manuel Álvarez, Alberto Pan, Juan Raposo, Fernando Bellas, Fidel Cacheda. Finding and Extracting Data Records from Web Pages. Journal of Signal Processing Systems (Special issue on EUC 2007). </li></ul></ul><ul><ul><li>Manuel Álvarez, Alberto Pan, Juan Raposo, Fernando Bellas, Fidel Cacheda: Extracting lists of data records from semi-structured web pages. Data Knowl. Eng. 64(2): 491-509 (2008) </li></ul></ul><ul><ul><li>Manuel Álvarez, Alberto Pan, Juan Raposo, Fernando Bellas, Fidel Cacheda: Using Clustering and Edit Distance Techniques for Automatic Web Data Extraction. WISE 2007: 212-224 </li></ul></ul><ul><ul><li>Juan Raposo, Alberto Pan, Manuel Álvarez, Justo Hidalgo: Automatically maintaining wrappers for semi-structured web sources. Data Knowl. Eng. 61(2): 331-358 (2007) </li></ul></ul><ul><li>Focused Crawling </li></ul><ul><ul><li>Manuel Álvarez, Juan Raposo, Alberto Pan, Fidel Cacheda, Fernando Bellas, Victor Carneiro: DeepBot: a focused crawler for accessing hidden web content. DEECS 2007: 18-25 </li></ul></ul><ul><ul><li>Manuel Álvarez, Juan Raposo, Alberto Pan, Fidel Cacheda, Fernando Bellas, Victor Carneiro: Crawling the Content Hidden Behind Web Forms. ICCSA (2) 2007: 322-333 </li></ul></ul><ul><li>Cost Optimization </li></ul><ul><ul><li>Justo Hidalgo, Alberto Pan, José Losada, Manuel Álvarez. Preloading Browsers for Optimizing Automatic Access to Hidden Web: a Ranking-based Repository Solution. ADBIS 2006. pp.171-183. </li></ul></ul><ul><ul><li>Justo Hidalgo, Alberto Pan, Manuel Álvarez, Jaime Guerrero. Efficiently Updating Cost Repository Values for Query Optimization on Web Data Sources in a Mediator/Wrapper Environment. NGITS 2006. Vol. 4032, pp. 1-12. </li></ul></ul>
    26. 28. Q&A Justo Hidalgo VP Product Management and Consulting [email_address]
    27. 29. <ul><li>All images shown that are not property of Denodo come from the search engine search.creativecommons.org, that searches Flickr images with CreativeCommons license </li></ul>Credits

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