Imagine an organization that manufactures and sells goods in several States of USA which employs hundreds of employees in its manufacturing, sales and marketing division etc. In order to manufacture and sell this product in profitable manner, the executives need to analyse (OLAP analysis) the data on the product and think about various possibilities and causes for a particular event like loss in sales, less productivity or increase in sales over a particular period of the year.
During the OLAP analysis, the top executives may seek answers for the following:
1. Number of products manufactured.
2. Number of products manufactured in a location.
3. Number of products manufactured on time basis within a location.
4. Number of products manufactured in the current year when compared to the previous year.
5. Sales Dollar value for a particular product.
6. Sales Dollar value for a product in a location.
7. Sales Dollar value for a product in a year within a location.
8. Sales Dollar value for a product in a year within a location sold or serviced by an employee.
OLAP tools help executives in finding out the answers, not only to the above mentioned measures, even for the very complex queries by allowing them to slice and dice, drill down from higher level to lower level summarized data, rank, sort, etc.
Time Dimension Id | Location Dimension Id | Product Dimension Id | Organization Dimension Id | Sales Dollar | DateTimeStamp |
---|---|---|---|---|---|
1 | 1 | 100001 | 1 | 1000 | 1/1/2005 11:23:31 AM |
3 | 1 | 100001 | 1 | 750 | 1/1/2005 11:23:31 AM |
1 | 1 | 100001 | 2 | 1000 | 1/1/2005 11:23:31 AM |
3 | 1 | 100001 | 2 | 750 | 1/1/2005 11:23:31 AM |
In the above example of OLAP analysis, data can be sliced and diced, drilled up and drilled down for various hierarchies like time dimension, location dimension, product dimension, and organization dimension. This would provide the topmost executives to take a decision about the product performance in a location/time/organization. In OLAP reports, Trend analysis can be also made by comparing the sales value of a particular product over several years or quarters.
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