Refer to BI overview, we found that business intelligence is used to support effective decision making. It provides foundational information on which to base a decision. Business intelligence also provides us with feedback information that can be used to evaluate a decision. It can provide that foundational and feedback information in a number of different ways.
When We know What We Are Looking For
- Printed Report or Layout-Led Discovery
When we know the question we want answered and have a good idea where that answer is going to be found, we can use printed reports to deliver our business intelligence. This is the most common form of business intelligence and one we are all familiar with. For many situations, this format works well. With layout-led discovery, we can only learn information that the report designer thought to put in the report layout when it was first designed. If the information wasn’t included at design time, we have no way to access it at the time the report is read.
- Drilldown Mechanism or Data-Led Discovery
In some cases, we know the question, but we don’t know exactly where to look for our answer. An anomaly in the information may cause us to want to look at the data in a slightly different way. In other cases, we know where to look, but it is not practical to search through all of the detailed information. Instead, we want to start at an upper level, find a number that looks interesting, and then drill to more detail. We want to follow the data that catches our attention to see where it leads.
This is data-led discovery: the information we find determines where we want to go next. The developer must provide an interactive environment that enables the user to navigate at will.
To implement data-led discovery, we need some type of drilldown mechanism. When we see something that looks interesting, we need to be able to click on that item and access the next level of detail. This is, of course, not going to happen on a sheet of paper. Data-led discovery must be done online.
Discovering New Questions and Their Answers
In some cases, our data may hold answers to questions we have not even thought to ask. The data may contain trends, correlations, and dependencies at a detail level, which would be impossible for a human being to notice using either layout-led or data-led discovery. These relationships can be discovered by the computer using data mining techniques.
| Definition | Data mining uses a complex mathematical algorithm to sift through detail data to identify patterns, correlations, and clustering within the data. |
Where layout-led discovery and data-led discovery usually start with summarized data, data mining works at the lowest level of detail. Highly sophisticated mathematical algorithms are applied to the data to find correlations between characteristics and events. Data mining can uncover such nuggets as the fact that a customer who purchased a certain product is more likely to buy a different product from your organization (we hope a product with a high profit margin). Or, a client receiving a particular service is also likely to need another service from your organization in the next three months.
This type of information can be extremely helpful when planning marketing campaigns, setting up cross-product promotions, or doing capacity planning for the future. It can also aid in determining where additional resources and effort would produce the most effective result
Source : Delivering Business Intelligence with Microsoft SQL Server 2005 – McGraw-Hill/Osborne