A Dimension represents a set of contextual data about the transactional data that is stored in the fact table(s). It basically forms the story line around the data by providing context and thereby helping the users to understand and make sense out of the data.
Example: Let us say that there is a retail chain and the CFO of the chain announces that the "Total Sales is $10,00,000". In this case, $10,00,000 is merely a number and does not provide any valuable information and does not make any sense to the user.
Now let us say that the CFO of the chain makes a slight change in the above announcement and says "Total Sales for FY 2012 is $10,00,000". This makes some sense and provides some amount of context which in this case is sales amount mentioned is for Financial Year 2012 (FY2012). FY2012 represents a date (time) component and hence it represents a Date (Time) Dimension.
Similarly, we can go on and add additional Dimensions to this data (Fact Table/Cube) to provide more context about the data (in this scenario $10,00,000 is the data we are talking about). Say we change the above statement to something like "Total Sales of Facial Tissues for FY 2012 in California is $10,00,000". This gives much better context compared to the previous two statements. In this statement, Facial Tissues represents a Product which introduces us to Product Dimension and California represents a Geographical Location which introduces us to Geography Dimension. In this manner, we can add as many dimensions as we want, to give better context to the data, so that end users can analyze the data from different dimensions and take more effective decisions.
Here are some highlights of Dimension(s):
It represents contextual information which adds context/meaning to the data being analyzed.
Helps in viewing/analyzing the data from different dimensions/angles to get a better understanding of the data.
A dimension is organized in the form of Attributes and Hierarchies.
Here are some examples of a Dimension:
Time Dimension
Product Dimension
Geography Dimension
Customer Dimension
Employee Dimension
Here are some examples of a Dimension Attribute
Year, Quarter, Month etc. in case of a Time Dimension
Color, Size etc. in case of a Product Dimension
Example: Let us say that there is a retail chain and the CFO of the chain announces that the "Total Sales is $10,00,000". In this case, $10,00,000 is merely a number and does not provide any valuable information and does not make any sense to the user.
Now let us say that the CFO of the chain makes a slight change in the above announcement and says "Total Sales for FY 2012 is $10,00,000". This makes some sense and provides some amount of context which in this case is sales amount mentioned is for Financial Year 2012 (FY2012). FY2012 represents a date (time) component and hence it represents a Date (Time) Dimension.
Similarly, we can go on and add additional Dimensions to this data (Fact Table/Cube) to provide more context about the data (in this scenario $10,00,000 is the data we are talking about). Say we change the above statement to something like "Total Sales of Facial Tissues for FY 2012 in California is $10,00,000". This gives much better context compared to the previous two statements. In this statement, Facial Tissues represents a Product which introduces us to Product Dimension and California represents a Geographical Location which introduces us to Geography Dimension. In this manner, we can add as many dimensions as we want, to give better context to the data, so that end users can analyze the data from different dimensions and take more effective decisions.
Here are some highlights of Dimension(s):
It represents contextual information which adds context/meaning to the data being analyzed.
Helps in viewing/analyzing the data from different dimensions/angles to get a better understanding of the data.
A dimension is organized in the form of Attributes and Hierarchies.
Here are some examples of a Dimension:
Time Dimension
Product Dimension
Geography Dimension
Customer Dimension
Employee Dimension
Here are some examples of a Dimension Attribute
Year, Quarter, Month etc. in case of a Time Dimension
Color, Size etc. in case of a Product Dimension
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