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The Siebel Analytics Server and Business Modeling

The Siebel Analytics Server is the core server behind Siebel Analytics. Siebel Analytics provides the power behind Siebel Intelligence Dashboards for access and analysis of structured data that is distributed across an organization or an the supply chain for an organization. The Analytics server allows a single information request to query multiple data sources, providing information access to members of the enterprise and, in Web-based applications, to suppliers, customers, prospects, or any authorized user with Web access.

Business organizations often find that the success of a strategic or tactical initiative depends on correctly monitoring, predicting, and understanding business events. Organizations also find that the use of technology to provide information to support decisions is critical. Providing that information with the appropriate technology remains, however, a significant challenge.

Given this complexity, analysis comes to a standstill—or worse, proceeds with inaccurate or misinterpreted results. In cases where attempts are made to solve this problem, the result is often a collection of stand-alone data marts designed to answer the current needs of a particular user group. Subsequent user groups trying to answer business questions might not know of the existence of these data marts, might find more than one data mart that partially answers their questions, or might find more than one that answers the questions with different results.

Business Model to SQL

The Siebel Analytics Server presents a business model that is accessible through structured query language (SQL). SQL is the standard interface to enterprise relational database management systems (RDBMS). Because the business model presented can be a simple one, you can query these models with simple SQL.

The Siebel Analytics Server provides a bridge from the simple SQL needed to query the business model to the often complicated SQL needed to extract the requested information from the underlying databases. It builds this bridge through the following methods:

Business models are dimensional models. Dimensions describe the attributes and hierarchies of the business. The models also include business measures useful for monitoring or predicting business performance. Because they mirror the way people think about business information, dimensional models can be understood by nontechnical business analysts.

The SQL required to query a Siebel Analytics Server business model is even less complex than the SQL required to query an RDBMS dimensional model. Join information, aggregation functions, and Group By clauses are not needed when querying through the Analytics server. Its server-side capabilities, together with its data modeling capabilities, provide that bridge, which allows simple SQL to pose complex business questions, regardless of where the data is physically located and independent of the physical model in which the data is stored.


 Siebel Analytics Server Administration Guide
 Published: 11 March 2004