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7: Data and Process Modeling
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19 The components of the CRUD matrix are A Ellipses to show attributes B Major processes shown on one axis C Major entities shown on the other axis D Reference numbers to show the hierarchy of processes E Letters to show the operations that processes carry out on entities 20 The CRUD matrix helps find the following problems: A Entities that are never read B Processes that are never deleted C Processes that only read D Entities that are never updated E Processes that have no create entity
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Physical Database Design
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Databases: A Beginner s Guide
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Designing Tables Integrating Business Rules and Data Integrity Designing Views Adding Indexes for Performance
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s introduced in 5 (Figure 5-1), once the logical design phase of a project is complete, it is time to move on to physical design Other members of a typical project team will define the hardware and system software required for the application system We will focus on the database designer s physical design work, which is transforming the logical database design into one or more physical database designs For situations in which an application system is being developed for internal use, it is normal to have only one physical database design for each logical design However, if the organization is a software vendor, for example, the application system must run on all the various platform and RDBMS versions that the vendor s customers use, and that requires multiple physical designs This chapter covers each of the major steps involved in physical database design
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The first step in physical database design is to map the normalized relations shown in the logical design to tables The importance of this step should be obvious, because tables are the primary unit of storage in relational databases However, if adequate work was put into the logical design, then translation to a physical design is much easier As you work through this chapter, keep in mind that 2 contains an introduction to each component in the physical database model, and 4 contains the SQL syntax for the Data Manipulation Language (DML) commands required to create the various physical database components (tables, constraints, indexes, views, and so on) Briefly, the process goes as follows:
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1 Each normalized relation becomes a table A common exception to this occurs when
super types and subtypes are involved, as discussed in the next section
2 Each attribute within the normalized relation becomes a column in the corresponding
table Keep in mind that the column is the smallest division of meaningful data in the
8: Physical Database Design
database, so columns should not have subcomponents that make sense by themselves For each column, the following must be specified:
A unique column name within the table Generally, the attribute name from the logical design should be adapted as closely as possible However, adjustments may be necessary to work around database reserved words and to conform to naming conventions for the particular RDBMS being used You might notice some column name differences between the Customer relation and the CUSTOMER table in the example that follows The reason for this change is discussed in the Naming Conventions section later in this chapter A data type, and, for some data types, a length and perhaps a precision Data types vary from one RDBMS to another, so this is why different physical designs are needed for each RDBMS to be used Whether column values are required or not This takes the form of a NULL or NOT NULL clause for each column Be careful with defaults they can fool you For example, when this clause is not specified, Oracle assumes NULL, but Sybase ASE and Microsoft SQL Server assume NOT NULL (although this default behavior can be changed for an instance or database) It s always better to specify such things and be certain of what you are getting Check constraints These may be added to columns to enforce simple business rules For example, a business rule specifying that the unit price on an invoice must always be greater than or equal to zero can be implemented with a check constraint, but a business rule requiring the unit price to be lower in certain states cannot use a check constraint Generally, a check constraint is limited to comparison of a column value with a single value, a range or list of values, or other column values in the same row of table data
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