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Figure 8-3: An entity s primary key is the attribute or group of attributes that uniquely identifies it. Notice how Subscription now has a primary key consisting of the foreign keys contributed from its relationships with the Customer and Newsletter entities Keep this in mind as we discuss relationship types a little later in this chapter. What you see in this figure is a Logical Data Model (or LDM) that, as its name suggests, shows how the logical entities in your database are structured and how they relate to one another. Notice how we developed the LDM from the ground up in layers. We started by considering only which entities were involved in the business processes and not how they were structured. This distinction may seem trivial at first, but it forces you to concentrate on exactly which entities your database manipulates and stores, and this may not be obvious on some larger database models because of the sheer number of business processes that they must support.

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SaIesOrder Customer CustomerNumber CustomerTypeCode (FK) CompanyName Lastname Firstname Middlename SalesOrderlD CustomerNumber (FK) SoldTo SaleDate Subtotal TaxRate TaxAmount Total

Subscription CustomerNumber (FK) NewsletterCode (FK) StartDate DurationMonths Price OrderItem ItemNumber SalesOrderID (FK) Description UnitPrice Quantity

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Figure 8-4: A relationship migrates a copy of the parent s primary key to the child entity as its foreign key. Next, we layered in the attributes that describe each of these entities and then decided which attributes should be used as their keys. From there, we declared relationships between the entities so that we could visualize the interaction between them. We get a better feel for how the software must accommodate these entities once relationships are declared, and we start to think forward to the user interface for creating and editing them.

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Something else that gives us good insight into how the software works with the database is identifying which attributes are absolutely necessary to describe each entity. If an attribute must be present to effectively describe an entity, that attribute cannot contain a NULL value. NULL values have wider significance than may first come to mind; if an attribute cannot be NULL, its value must be acquired during all business processes that create those entities. You may find that significant changes to business processes become necessary just so that you can create correctly defined entities in your database.

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It may seem backward to most readers, but waiting until last to consider attributes data types makes perfect sense. In the same way that considering entities separately from their structure in the beginning of the engineering process helped you to concentrate without distraction, waiting until the last minute to consider attribute data types prevents you from being distracted from more important design issues, such as which attributes are critical to describing the entities to which they belong. If you always engineer your databases by using this layered approach, the Web applications that they support are easier to code, require less maintenance, and perform faster. To recap, you want to follow these steps in the process of creating a relational database: 1. Define the entities that your business processes use. 2. Determine which attributes describe each entity. 3. Determine which attribute or combination of attributes of each entity is the key that uniquely identifies every instance of that entity. 4. Declare the relationships between entities. 5. Determine which attributes of each entity are considered critical to the description of that entity. 6. Define the data type for each attribute. The preceding six steps are always performed regardless of the target database platform (SQL Server, Oracle, etc.) on which you plan to deploy your database. You may also perform two additional steps in modeling your database, but these steps we cover in the sections Defaults and Check Constraints, later in this chapter. After you have a basic, logical data model, you need to describe a few details about how its relationships work. Then you go about extracting your Physical Data Model, or PDM, from the logical data model and describe the differences between them and why they are significant. The following sections detail how to go about these processes.

The electric potential difference between two points (2 and 1) in the electrolyte during diffusion is thus given by the equation

Relationships are described by four attributes: cardinality, identification, optionality, and degree. These attributes are combined to create specific relationship types, as you will see in the section Types of relationships.

Cardinality describes the quantitative dimension of the relationship as viewed from the parent table s perspective. The relationship between the CustomerType and Customer

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