Determine scope of business intelligence analysis

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Applies To: Office SharePoint Server 2007

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Topic Last Modified: 2016-11-14

In this article:

  • About business intelligence scope planning

  • Business intelligence principles

  • Business intelligence examples

About business intelligence scope planning

Business intelligence is the process of gathering, storing, analyzing, and accessing business data across an organization. Microsoft SQL Server 2005 provides a storage and management foundation for business data, and a set of reporting and analysis tools. Microsoft Office SharePoint Server 2007 provides controlled access to — and analysis of — business data, and the ability to leverage data to make better business decisions. Office SharePoint Server 2007 supports workflow, document management, search, data integration, data analysis, and data rendering. It enables you to maintain data integrity and centrally manage shared resources that can include reports, forms, documents, spreadsheets, and data connections.

The Microsoft BI stack is an end-to-end solution built on Microsoft SQL Server 2005, Office SharePoint Server 2007, 2007 Microsoft Office system client applications, and performance management products provided by the Office Business Applications group.

SQL Server 2005 is the data storage and analysis foundation of the Microsoft BI stack. SQL Server 2005 provides relational database management system (RDBMS) data storage, and a set of management tools including:

  • SQL Server 2005 Analysis Services

  • SQL Server 2005 Integration Services

  • SQL Server 2005 Reporting Services

  • SQL Server 2005 Business Intelligence Development Studio

Business intelligence principles

The principles of business intelligence in Office SharePoint Server 2007 include:

  • Data gathering   Integrating data from various structured and unstructured sources.

  • Data storage   providing a secure, centrally managed data repository.

  • Data analysis   Creating hierarchical views to enhance data discovery and rendering data that can be understood in business terms.

  • Data access   Improving data quality and ensuring data integrity by providing secure access to shared data resources in a collaborative workspace.

  • Data cleansing   Ensuring that data from the source makes sense, is not duplicated, and does not contain null values.

  • Extract, Transform, and Load (ETL)   Extracting data from source databases, transforming data into the structures used in targeted databases, and loading data into targeted databases.

Business intelligence examples

Some examples of business intelligence solutions include:

  • Predictive analysis   Determining the probable outcome of an event or the likelihood of a database state using information that is extrapolated from a known data set.

  • Data mining   Sorting through data to identify patterns and establish cause-and-effect relationships.

  • Sales forecasting   Reviewing current account status or customer characteristics and making adjustments based on live data.

  • Purchase order approval   Checking current budget status and other data before approving a workflow-generated purchase order.

  • Closed-loop analysis   Continuously tracking and improving the quality and performance of products and processes based on feedback. Closed-loop analysis enables you to align the day-to-day operations of an organization with a long-term business strategy. You can use closed-loop analysis to make data more discoverable and actionable.

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