Dimension Table
Dimension table is one that describes the business entities of an enterprise, represented as hierarchical, categorical information such as time, departments, locations, and products. Dimension tables are sometimes called lookup or reference tables.
Location Dimension
In a relational data modeling, for normalization purposes, country lookup, state lookup, county lookup, and city lookups are not merged as a single table. In a dimensional data modeling (star schema), these tables would be merged as a single table called LOCATION DIMENSION for performance and slicing data requirements. This location dimension helps to compare the sales in one region with another region. We may see good sales profit in one region and loss in another region. If it is a loss, the reasons for that may be a new competitor in that area, or failure of our marketing strategy etc.
Example of Location Dimension: Country Lookup
Country Code Country Name DateTimeStamp
USA United States Of America 1/1/2005 11:23:31 AM State Lookup
State Code State Name DateTimeStamp NY New York 1/1/2005 11:23:31 AM FL Florida 1/1/2005 11:23:31 AM CA California 1/1/2005 11:23:31 AM NJ New Jersey 1/1/2005 11:23:31 AM County Lookup
County Code County Name DateTimeStamp NYSH Shelby 1/1/2005 11:23:31 AM FLJE Jefferson 1/1/2005 11:23:31 AM
CAMO Montgomery 1/1/2005 11:23:31 AM NJHU Hudson 1/1/2005 11:23:31 AM City Lookup
City Code City Name DateTimeStamp
NYSHMA Manhattan 1/1/2005 11:23:31 AM FLJEPC Panama City 1/1/2005 11:23:31 AM CAMOSH San Hose 1/1/2005 11:23:31 AM NJHUJC Jersey City 1/1/2005 11:23:31 AM Location Dimension Location Dimension Id Country Name State Name County Name City Name DateTime Stamp
1 USA New York Shelby Manhattan 1/1/2005 11:23:31 AM 2 USA Florida Jefferson Panama City 1/1/2005 11:23:31 AM 3 USA California Montgomery San Hose 1/1/2005 11:23:31 AM 4 USA New Jersey Hudson Jersey City 1/1/2005 11:23:31 AM Product Dimension
In a relational data model, for normalization purposes, product category lookup, product sub- category lookup, product lookup, and and product feature lookups are are not merged as a single table. In a dimensional data modeling(star schema), these tables would be merged as a single table called PRODUCT DIMENSION for performance and slicing data requirements.
Example of Product Dimension: Figure 1.9 Product Category Lookup
Product Category Code Product Category Name DateTimeStamp 1 Apparel 1/1/2005 11:23:31 AM
2 Shoe 1/1/2005 11:23:31 AM Product Sub-Category Lookup Product
Sub-Category Code Product Sub-Category Name DateTime Stamp 11 Shirt 1/1/2005 11:23:31 AM 12 Trouser 1/1/2005 11:23:31 AM 13 Casual 1/1/2005 11:23:31 AM 14 Formal 1/1/2005 11:23:31 AM Product Lookup
Product Code Product Name DateTimeStamp 1001 Van Heusen 1/1/2005 11:23:31 AM 1002 Arrow 1/1/2005 11:23:31 AM 1003 Nike 1/1/2005 11:23:31 AM 1004 Adidas 1/1/2005 11:23:31 AM Product Feature Lookup
Product Feature Code Product Feature Description DateTimeStamp 10001 Van-M 1/1/2005 11:23:31 AM
10002 Van-L 1/1/2005 11:23:31 AM 10003 Arr-XL 1/1/2005 11:23:31 AM 10004 Arr-XXL 1/1/2005 11:23:31 AM 10005 Nike-8 1/1/2005 11:23:31 AM 10006 Nike-9 1/1/2005 11:23:31 AM 10007 Adidas-10 1/1/2005 11:23:31 AM 10008 Adidas-11 1/1/2005 11:23:31 AM Product Dimension
Product Dimension Id Product Category Name Product Sub-Category Name Product Name Product Feature Desc DateTime
Stamp
100001 Apparel Shirt Van Heusen Van-M 1/1/2005 11:23:31 AM 100002 Apparel Shirt Van Heusen Van-L 1/1/2005 11:23:31 AM 100003 Apparel Shirt Arrow Arr-XL 1/1/2005 11:23:31 AM 100004 Apparel Shirt Arrow Arr-XXL 1/1/2005 11:23:31 AM 100005 Shoe Casual Nike Nike-8 1/1/2005 11:23:31 AM 100006 Shoe Casual Nike Nike-9 1/1/2005 11:23:31 AM 100007 Shoe Casual Adidas Adidas-10 1/1/2005 11:23:31 AM 100008 Shoe Casual Adidas Adidas-11 1/1/2005 11:23:31 AM Organization Dimension
In a relational data model, for normalization purposes, corporate office lookup, region lookup, branch lookup, and employee lookups are not merged as a single table. In a dimensional data modeling(star schema), these tables would be merged as a single table called ORGANIZATION DIMENSION for performance and slicing data.
This dimension helps us to find the products sold or serviced within the organization by the employees. In any industry, we can calculate the sales on region basis, branch basis and employee basis. Based on the performance, an organization can provide incentives to employees and subsidies to the branches to increase further sales.
Example of Organization Dimension: Figure 1.10 Corporate Lookup
Corporate Code Corporate Name DateTimeStamp CO American Bank 1/1/2005 11:23:31 AM Region Lookup
Region Code Region Name DateTimeStamp SE South East 1/1/2005 11:23:31 AM MW Mid West 1/1/2005 11:23:31 AM Branch Lookup
Branch Code Branch Name DateTimeStamp FLTM Florida-Tampa 1/1/2005 11:23:31 AM ILCH Illinois-Chicago 1/1/2005 11:23:31 AM Employee Lookup
Employee Code Employee Name DateTimeStamp E1 Paul Young 1/1/2005 11:23:31 AM
E2 Chris Davis 1/1/2005 11:23:31 AM Organization Dimension
Organization Dimension Id Corporate Name Region Name Branch Name Employee Name DateTime Stamp
1 American Bank South East Florida-Tampa Paul Young 1/1/2005 11:23:31 AM 2 American Bank Mid West Illinois-Chicago Chris Davis 1/1/2005 11:23:31 AM Time Dimension
In a relational data model, for normalization purposes, year lookup, quarter lookup, month lookup, and week lookups are not merged as a single table. In a dimensional data modeling(star schema), these tables would be merged as a single table called TIME DIMENSION for performance and slicing data.
This dimensions helps to find the sales done on date, weekly, monthly and yearly basis. We can have a trend analysis by comparing this year sales with the previous year or this week sales with the previous week.
Example of Time Dimension: Figure 1.11 Year Lookup
Year Id Year Number DateTimeStamp 1 2004 1/1/2005 11:23:31 AM 2 2005 1/1/2005 11:23:31 AM Quarter Lookup
Quarter Number Quarter Name DateTimeStamp 1 Q1 1/1/2005 11:23:31 AM
2 Q2 1/1/2005 11:23:31 AM 3 Q3 1/1/2005 11:23:31 AM 4 Q4 1/1/2005 11:23:31 AM Month Lookup
Month Number Month Name DateTimeStamp 1 January 1/1/2005 11:23:31 AM 2 February 1/1/2005 11:23:31 AM 3 March 1/1/2005 11:23:31 AM 4 April 1/1/2005 11:23:31 AM 5 May 1/1/2005 11:23:31 AM 6 June 1/1/2005 11:23:31 AM 7 July 1/1/2005 11:23:31 AM 8 August 1/1/2005 11:23:31 AM 9 September 1/1/2005 11:23:31 AM 10 October 1/1/2005 11:23:31 AM 11 November 1/1/2005 11:23:31 AM 12 December 1/1/2005 11:23:31 AM Week Lookup
Week Number Day of Week DateTimeStamp 1 Sunday 1/1/2005 11:23:31 AM 1 Monday 1/1/2005 11:23:31 AM 1 Tuesday 1/1/2005 11:23:31 AM 1 Wednesday 1/1/2005 11:23:31 AM 1 Thursday 1/1/2005 11:23:31 AM 1 Friday 1/1/2005 11:23:31 AM 1 Saturday 1/1/2005 11:23:31 AM 2 Sunday 1/1/2005 11:23:31 AM 2 Monday 1/1/2005 11:23:31 AM 2 Tuesday 1/1/2005 11:23:31 AM
2 Wednesday 1/1/2005 11:23:31 AM 2 Thursday 1/1/2005 11:23:31 AM 2 Friday 1/1/2005 11:23:31 AM 2 Saturday 1/1/2005 11:23:31 AM Time Dimension
Time Dim Id Year No Day of Year Quarter No Month No Month Name Month Day No Week No Day of Week Cal Date DateTime
Stamp
1 2004 1 Q1 1 January 1 1 5 1/1/2004 1/1/2005 11:23:31 AM 2 2004 32 Q1 2 February 1 5 1 2/1/2004 1/1/2005 11:23:31 AM 3 2005 1 Q1 1 January 1 1 7 1/1/2005 1/1/2005 11:23:31 AM 4 2005 32 Q1 2 February 1 5 3 2/1/2005 1/1/2005 11:23:31 AM
Posted 19th December 2011 by Prafull Dangore 0 Add a comment 32.