When decision-makers implement a business intelligence solution to help in their analytical tasks, they use the system with different scopes of analysis. They start their day faced with business decisions to solve problems, or opportunities, such as identifying the most profitable customers, determining the products with low margins or choosing the ideal price point for a product offering. Without a business intelligence solution that provides efficient reports and charts for different business processes, this sort of analysis becomes a long and tedious task involving spreadsheet software products. With state-of-the-art software, the task becomes easier. Still, the true "intelligent" component of a BI solution is not in the efficiencies of grouping and displaying data at the summary and detail level; the "intelligence" is a combination of technology and identifying the appropriate scope of analysis and decision-making paths when faced with a business decision.
When a business manager starts her day, she starts looking at a few reports which are identified as "most important" for her. These reports are usually at the aggregate level. The level of this aggregation increases as the individual using the system has greater responsibilities in a more senior role in the organization. She starts looking at these key reports and drills down to a lower level of detail or across to another report. She may identify some key factors, maybe some short-term trends, look at some more reports and run some ad hoc queries. She may still need some other reports, so she might look at some cross-functional data residing in a nearby data mart. When she finds enough data as the basis for her task, she identifies some alternatives and makes a business decision.
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