All application systems, as well as the data warehouse, contain information based on the data used by the company. The business data model represents that data and is the foundation for all systems’ models, including the data warehouse model.
A fully developed business data model may contain hundreds of entities. A subject area model, which defines the major groupings of information, is a good way to manage these entities by providing a logical approach for grouping the entities.
This chapter begins by describing the subject area model, with particular emphasis on how it helps ensure consistency and manage redundancy in the data warehouse model.
The section on the business data model dispels these concerns and demonstrates that this model is a means of describing the business in a shorthand notation (that is, rectangles and lines) that facilitates the subsequent development of supporting application systems.
This is a “how to” book on data warehouse modeling. the modeling concepts will be demonstrated using practical scenarios. We use a business scenario to demonstrate the modeling activities.
Business Scenario
We use a business scenario of an automobile manufacturer to develop the subject area model and business data model in this chapter and the data ware- house data model in Chapter 4. Following the description of the business scenario, we will dive into the subject area model.
Our automotive manufacturing firm is named Zenith Automobile Company (ZAC). ZAC was founded in 1935, and manufactures two makes of automobile—Zeniths and the higher-end luxury Tuxedos. Each of these makes have models that describe the type of car, and each model has three series available. The models are described in Table
All of ZAC’s cars are sold through dealers throughout the United States. Dealers are independent entities, but to retain their right to serve as ZAC dealers, they are governed by ZAC’s rules. One of those rules requires them to submit monthly financial statements. The dealers are located within sales areas, which are grouped into sales territories, which are grouped into sales regions. Allocations are made at the sales area level, and incentive programs are developed by ZAC corporate.
Over the years, ZAC has developed a myriad of systems on mainframes, mini- computers, and even PCs. It built and/or bought other automobile manufacturing facilities, which resulted in even more disparate systems and databases.
Currently, it has IBM 3090s, DEC VAXs, Tandems, Suns, and HPs, plus PCs and Macintoshes. Their data is spread out in DB2, VSAM and enscribe files, Non-stop SQL, RDB, Oracle, Sybase, and Informix. End users have tools such as Paradox, R-base, Microsoft Access, and Lotus Notes. Needless to say, the data is spread out in hundreds of disparate databases throughout the company, with many in inaccessible formats.
Based on interviews with key stakeholders, the ZAC decided to undertake development of a data ware- house and a set of data marts that could answer the following questions :
=> What is the monthly sales trend in terms of quantity and dollar amounts sold of each make, model, series, and color (MMSC) for a specific dealer, by each sales area, sales territory, and sales region, for each state and for each metropolitan statistical area (MSA)?
=> What is the pattern in the monthly quantity of inventory by MMSC for each dealer, by each sales area, sales territory, sales region, and MSA?
=> How does the monthly quantity and dollars of sold automobiles by MMSC having a particular emissions type—by Dealer, Factory, Sales Area, Sales Territory, and Sales Region—compare with the same time frame last year and the year before?
=> What is the trend in monthly actual sales (dollars and quantities) of MMSC for each dealer, sales area, sales territory, and sales region com- pared to their objectives? Users require this information both by monthly totals and cumulative year to date (YTD).
=> What is the history (two-year comparisons) of the monthly quantity of units sold by MMSC and associated dollar amounts by retail versus wholesale dealers?
=> What are the monthly dollar sales and quantities by MMSC this year to date as compared to the same time last year for each dealer?
=> What is the monthly trend in sales dollars and quantities by MMSC for particular types of incentive programs, by dealer, sales area, sales territory, sales region, and MSA?
=> What is the monthly trend in the average time it takes a dealer to sell a particular MMSC (called velocity and equal to the number of days from when a dealer receives the car to the date it is sold) by sales area, sales territory, sales region, and MSA?
=> What was the monthly average selling price of an MMSC for each dealer, sales area, sales territory, sales region, and MSA?
=> How many days was a dealer placed on credit hold for this month only and for the entire year? In addition, what was the total number of months in the past two years that the dealer was put on credit hold?
=> Compare monthly sales dollars and quantities from the last body style (body style is make + model) to the current body style for each sales region? Body styles change every four years.
Subject Area Model
A data warehouse is organized by subject area, so it is only natural that the methodology for a data warehouse data model should begin with the subject area model. The subject-orientation of the data warehouse distinguishes it from a traditional application system. In the traditional operational system, although the data model should begin with a subject area model, this step is often omitted. Since the operational system is oriented toward specific business functions and processes, its design needs to emphasize the efficiency with which it can process the related transactions.
We also indicated that the subject area model can be developed very quickly. An organization developing its first subject area model can benefit from work per- formed by others so that it doesn’t need to start from scratch. There are many subject areas that are common across industries; virtually all organizations have customers, suppliers, products, and facilities. These are candidates for subject areas.
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