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Enabling Data as a Service with the JBoss Enterprise Data Services Platform
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Enabling Data as a Service with the JBoss Enterprise Data Services Platform


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This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and …

This presentation was given at JUDCon 2013, Jan 17,18 at Bangalore. Presented by Prajod Vettiyattil and Gnanaguru Sattanathan. The presentation deals with the Why, What and How of Data Services and Data Services Platforms. It also explains the features of the JBoss Enterprise Data Services Platform.
The need for Data Services is explained with 3 Business use cases:
1. Post purchase customer experience improvement for an Auto manufacturer
2. Enterprise Data Access Layer
3. Data Services for Regulatory Reporting requirements like Dodd Frank

Published in: Technology

1 Comment
  • Hi Guru,

    Great that you made a presentation at JUDCon.

    Arumugam Subramanian
    Are you sure you want to  Yes  No
    Your message goes here
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  • 1. 1
  • 2. Enabling Data as a Service with JBoss Data Services Prajod Vettiyattil Gnanaguru Sattanathan Twitter: @prajods Twitter:@gnanagurus Website: bushorn.com2
  • 3. What this session is aboutThe why and what of data servicesHow data services workUse casesJBoss Data Services Platform3
  • 4. Why4
  • 5. Proliferation of data Data Consumers Custom Employee ERP CRM Accounting Billing er portal portal Partner Vendor Finance Marketing Sales Management Management Content Mainfra ManageSQL File NoSQL Email ERP me ment System Data Sources and Data Managers 5
  • 6. Proliferation: so what ?• Multiplicity of connections – High development cost – Huge operational overhead – Difficult and risky to change Data Sources/Managers• Dispersed data connectors• Data duplication – Too much ETL – Lines of Business copies data• Duplicated data aggregation• Impossible to create “Single source of truth”• Data ownership issues• No comprehensive view – No data movement dashboards – Location of data and its status6
  • 7. What7
  • 8. Data Services and DSP The basic view• DSP = Data Services Platform • Presents the data as a service to the• Abstracts the data consumer managers/sources • ETL++ C1 C2 C3 Data Consumers C4 C5 C6 Data Service 1 Data Service 2 Data Services Platform Data Service 3 Data Service 4 D1 D2 D3 Data Managers D4 D5 D68
  • 9. Dashboard in a DSP Data Data movement Errors Connections status Data Dashboard Error Failures Alerts Corrections9
  • 10. How it works10
  • 11. Features of a DSP• Enables architecture principles – Separation of concerns – Protected variations• Data adapters• Data mapping tools and standards• Data caching – Local and distributed• Service search and reuse• Data security and data usage audit• Data access control• Central channel for all data requirements• Data dashboard• Configurable performance and reliability11
  • 12. Use cases12
  • 13. Auto manufacturing supply chain: Requirements• Vehicle ownership experience• Business Process Automation• Disparate data sources• Multiple data feeds – Parts catalog – Prices• Dealer updates – Parts consumed – Parts replaced – Part failure statistics• Customer feedback – Post purchase – Breakdown support – Service Quality Dashboards• Integration solutions based on batch transfers – Unreliable – Not traceable13
  • 14. Auto manufacturing supply chain: Layer Diagram Customer Business Activity MonitoringExperienceDashboards Business Processes Enterprise Service Bus Data Services Platform PartsBreakdown Customer Parts Dealer Dealer supplier Customer reports feedback Catalog feeds feeds Info Master14
  • 15. Enterprise Data Access Layer: Requirements• Golden copy / System of Record / Single source of truth• Shared services team for Enterprise Data Management• Data usage audit• Data access control• Reduce request load on Data Management team• Reduce data maintenance costs15
  • 16. Enterprise Data Access Layer: Layer Diagram Enterprise Data Consumers Data Services Virtual DB Data Services Platform Metadata Data base Data Access Auditing Data Aggregation drivers Control Content PartnerMainframe Management Partner Customer Employee Data System Info Master Info16
  • 17. Reporting risk for securities: Requirements• Internal and external reporting – Risk and margin• Centralized risk capture and management• Calculate risk from different customer activities• Report consolidated data to comply with regulation – Dodd Frank – Sarbanes Oxley Act (SOX)• Dashboards for higher management17
  • 18. Reporting risk for securities: Architecture without DSP COTS Trading Customer Government Reporting Partner Apps Systems facing Apps Systems Applications Execution Liquidity Position Order Mgmt Order Book Mgmt Mgmt Mgmt Price feeds Enterprise Middleware Systems Trade feeds (MQ, ESB, FTP, File shares) Trade Ref Data Payment Margin Mgmt Clearing Matching Feeds Systems Custom built Risk Ref Data Settlement Accounting Apps Management Mgmt18
  • 19. Reporting risk for securities: Patterns in this requirement• Regulatory requirement for transparency – Cannot be met by opaque internal systems• Data Sources – Large number of them – Internal and external• Reports are read heavy• No real time data requirements – once a quarter or once a year• No excuses for incorrect data in reports• Non-discretionary spending19
  • 20. JBoss Data Services Platform20
  • 21. Architecture Data consumers (Custom Applications, COTS products, Business Processes, Business Services ) Data interfaces• The EDS platform (JCR API, Web service, JDBC, ODBC, OData,..) • Parts of the architecture – v5 Runs on SOA-P – Data interfaces• Teiid Metadata – Data adapters Data virtualization –• ModeShape repository Data virtualization – Metadata repository Data Adapters SOA Platform Data Services Platform SAP Sybase Flat file XML SalesFo Oracle Cassan Mongo rce dra DB Data Sources 21
  • 22. Data sources Oracle IBM MS MySQL PostgreS Sybase DB DB2 SQL QL Server Greenpl Teradata Netezza Ingres Mondria MetaMa um n trix LDAP Salesfor Delimite XML Web Apache ce d file file services Hive MS MS JBoss JBoss TIBCO IBM Excel Access Messagi HornetQ MQ ng22
  • 23. Data Mapping• Teiid Designer – Map actual data tables using transforms to virtual tables – MDD; use Data Models, not SQL – Semantic mapping – Virtual procedures • A set of SQL statements, similar to DB stored procedures23
  • 24. Data Standards• JCR – Java Content Repository(JSR-283)• OData – Open Data Protocol• JDBC• ODBC• Others – S-RAMP – An SOA repository spec, OASIS – Web Services – REST – JMS24
  • 25. Access control and Audit• Teiid – passwords – MembeshipDomains for authentication – Data roles • Fine grained access and visibility control of tables – CRUD level permissions for VDB – LDAP integration• ModeShape – LoginContext – AuthenticationProvider – Role to Action mapping25
  • 26. Teiid and ModeShape Data type Teiid ModeShape Approach Relational Hierarchical Metadata repository Not suitable Yes Content repository Not suitable Yes ACID transactions Yes Yes SQL queries Yes Yes(JCR-SQL) Flat file data source Yes Not suitable Relational DB data source Yes Not suitable Schema Fixed Optional NoSQL data sources Not suitable Yes Stores data No Yes26
  • 27. Summary• Data Services – Why – What – How• Use cases – Auto Manufacturer – Enterprise Data Access Layer – Regulatory Reporting• JBoss DSP – Data virtualization – Teiid – ModeShape27
  • 28. Questions Prajod Vettiyattil Gnanaguru Sattanathan Twitter: @prajods Twitter: @gnanagurus Website: Our Open Source Middleware Group on LinkedIn