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Componentized and modular |
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Service-implemented architecture |
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Built “from the ground up” as a set of services |
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Exposed via AJAX and Web Services |
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100% Java EE server side |
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Scalable, standards-based |
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Web-based, thin-client end user interfaces |
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Database: Oracle, SQLServer, MySQL, Postgres, etc. |
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Application Server: JBoss AS, Glassfish, Tomcat, WebSphere, etc. |
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ESB (if used): JBoss ESB, Apache ServiceMix, Mule, etc. |
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Graphical design interfaces |
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Embedded process workflow engine |
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Provides an abstraction layer between source systems and business user concepts |
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Graphical design environment for defining metadata model |
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Data presented to business users in business terms |
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Allows business users to create their own ad hoc reports based on centralized business rules, without any technical skills or knowledge of SQL |
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Changes to physical database do not impact reports or analytic views |
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Provides centralized maintenance for data connectivity, security, formatting, and more |
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Granular data access/Row-level security |
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Changes in BI metadata layer are automatically “inherited” when reports are re-run |
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eliminates manual maintenance of individual reports based on data infrastructure changes |
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Multi-lingual support |
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Define multiple language translations centrally |
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Automatically present to business users based on browser locale |
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 Scale-Out Architecture
In a scale-out architecture, commodity servers (typically 4, 8, or 16 CPU rack-mounted servers) are added to achieve the performance necessary. As more throughput is required servers are added one at a time. Because multiple BI servers are involved, a technology is needed to distribute work to each of these machines. This technology might be a load balancer or messaging system or an Enterprise Service Bus (ESB). Load balancers and other work distribution mechanisms introduce a performance overhead that typically decreases performance but increases scalability |
