Microsoft Corporation faced a gap in delivering accurate, timely, & easily consumable information to its sales force community. Sales force data was stored in SQL Server 2000 databases on multiple source systems including Siebel CRM. Those divergent data sources contained different aspects of sales data such as sale quotas in the incentive compensation system and sales opportunity information in the Siebel CRM system. Having the data in separate databases prevented the information from being utilized to its full potential.

Microsoft engaged an experienced project team to undertake a rapid transformation of the data into a more valuable tool for the sales community via Siebel Business Analytics. Rapid prototyping was a key Software Development Life Cycle (SDLC) element of the project approach due to timeline and limited functional requirements. This paper will describe that effort and provides insight into the critical success factors to target and the pitfalls to avoid during similar implementations.

The core Siebel Business Analytics technology stack will be reviewed with specific coverage of Siebel Analytics in a stand-alone implementation. Tuning and refresh considerations as well as describing the project physical and logical architecture will also be included. Database configuration considerations and suggestions for tuning for similar implementations will also be discussed. Since the disk subsystem is particularly critical for database application performance, recommendations & guidelines will be made for basic disk layout and the effective use of RAID technology. Additionally basic methodology and approach to the project will be discussed as it relates to Rapid Prototyping and the unique strengths of the Siebel Analytics/MS SQL Server setup, tuning, and integration advantages to support that approach.

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