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Browse back issues of SQL Server Pro, from January 2007 through the last issue published in April 2014.
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From small to large, companies need to keep track of supplies they use in the office and products they sell to their customers.
For my series of columns about metamodels, I defined a metamodel as a template—a data model of a generic situation (usually a business-related situation) from which you can derive and create models for your own database projects. So far in the series, I've developed metamodels for retail sales (May 2001), product assembly (June 2001), contact management (July 2001), reservations (October 2001), and scheduling (November 2001). Now, let's develop a metamodel that lets you do simple inventory control for an office, a store, or a warehouse.

To manage inventory, you need to determine how to track the products you carry product category that each product fits into quantity of each product you have in stock suppliers you order the products from products you have on order product reorder dates Figure 1 represents a conceptual view of the inventory-control metamodel, which incorporates the six kinds of data I identified. CATALOG contains not only information about products and product availability (which the PRODUCT_CATEGORY, PRODUCT, and SUPPLY_LIST entities represent) but also information about who manufactures the products (MANUFACTURER) and who distributes the products (SUPPLIER). The MANUFACTURER and SUPPLIER entities are both companies, so I chose a supertype-subtype architecture to represent these entities.
A supertype-subtype architecture is a way of organizing entities to show an inheritance-type relationship between them. For example, a manufacturer can license zero, one, or many suppliers to distribute its products, and a supplier can distribute products for one or many manufacturers.
One of the block's entities contains information about the location of each warehouse or store (WAREHOUSE), a second entity describes the individual storage bins or areas within each warehouse (WH_BIN), and a third entity lists all the products that are currently available in inventory (INVENTORY). Note that I've chosen to implement the subtype tables (MANUFACTURER and SUPPLIER) instead of the supertype table (COMPANY). Data modelers who implement the subtype table do so for one of two reasons: either the attribute sets of the subtype tables differ substantially or the subtype tables are involved in different types of relationships. Figure 3 shows that the subtype tables' attribute sets are similar, but the relationships that these tables have with other tables are different.
The EMPLOYEE table contains just enough information to identify the individual who placed the purchase order (employee identifier, name, and job title). You can cause synchronization problems by trying to keep totals coordinated when the values that make up the calculated column change.

However, I recommend using calculated columns when you can't accurately reconstruct the calculated value over time or when recalculating the total values in the table or in a query causes serious performance problems. This metamodel has no capacity for storing price history, so because I can't accurately reconstruct the calculated values over time, I included calculated columns in the PURCHASE_ORDER table. By using LineTotal, you can capture discounts, shipping methods, and estimated and actual delivery dates on an item-by-item basis. This deviation from the standard metamodel for retail sales gives you more flexibility for managing orders and lays the foundation for an item-backorder management system.
The assumption underlying this subschema is that you have one or more places where you store products, either for sale or for redistribution within your own company. The WAREHOUSE and INVENTORY tables share a M:N relationship, so each warehouse can house many inventory items, and inventory can be housed in one or many warehouses.
The PURCHASE_ORDER and WAREHOUSE subschemas work together to let you track the inventory you have on hand, the inventory you have on order, and the employees who placed the product orders and the orders to restock the inventory. In a future column, I'll expand this metamodel to include more complex inventory requirements, such as pricing controls, back ordering, and inventory movement between multiple warehouses.

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