Business Query
This refers to the set of queries that the warehouse would be expected to answer. Business queries define the structure and the usage of the warehouse. This is the reason that warehouse models follow a business model rather than the operational model used in transactional systems. A sample business query would be: ‘List all stores that showed a profit increase of over 10% for the northwest region for the last quarter’.
On-line Transaction Processing (OLTP) systems are the operational systems that record and process the day to day transactions. Hence they are always current. OLTP systems do not support adhoc queries because they store data mostly in Entity Relation model. (Ex. NM
Dimensional Model is the logical design technique often used for data warehouses. It contains the same information as an Entity Relation model but packages the data in a symmetric format whose design goals are user understandability, query performance and resilience to change.
FactFacts are the numerical measurements of the business. They are continuously valued and additive. The term ‘FACT’ refers to the subject areas that are to be analyzed. Consider an example in which a retail company wishes to employ a data warehouse. The ‘Facts’ for this warehouse would be the subject areas that the managers of the company would like to analyze (ex. Sales, Inventory, Profit etc). Examples for fact are cost price, sold price, units sold.
DimensionDimensions represent those data element that would be used for analyzing the Facts. For example, the above listed facts would be analyzed using the dimensions of Time (to provide time-based analysis), Geography (To provide performance analysis across regions), Product (To provide analysis across products). Dimensions will store the textual descriptions of the business. Examples are product definition attributes like color, size etc.
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