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An aggregate table must provide the same query results as the original schema. From a design perspective, the easiest way to guarantee this is to require that the aggregate star conform to the base star. This ensures semantic consistency across any common attributes, and equivalent content. It will also be necessary to enforce this conformance as part of the ETL process. In an aggregate schema, the conformance requirement applies both to dimension attributes and to facts. Dimensional conformance has already been discussed. As you learned in 5, two dimension tables conform if they are the same in structure and content, or if the attributes of one are a subset of the other and share common structure and content.

Creating a Table (CREATE TABLE)

Date 01/11/2000

By guaranteeing the same structure and content of common dimension attributes, the principle of conformance ensures that each replica represents the same thing Like dimensions, facts can conform As with conformed dimensions, conformed facts share a common structure and content Structural equivalence requires that the facts should have the same name, business meaning, and data type Content equivalence requires that they return the same information when aggregated to the same level of detail The facts in an aggregate schema conform with those of the base schema This ensures that the aggregate facts can be used interchangeably with the original facts, while guaranteeing consistent results TiP The facts and dimensions of an aggregate schema conform to those of the base schema This guarantees consistent results Following these guidelines, the dimension tables associated with order_facts_aggregate in Figure 15-1 must conform with those in the base star.

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Salesperson and product will be the same tables, or identical replicas The month table will be a conformed rollup of day, as depicted in Figure 5-5 This guarantees that dimensions from the base and aggregate star can be used interchangeably The facts in order_facts_aggregate must also conform to the base star Only one fact is shown: order_dollars It must have the same name and meaning as it does in the base star It should share the same data type, although it may require greater scale, since it is likely to hold larger numbers Content must also be the same Query results that include this fact should return the same results as those from the base fact table Order dollars by month, for example, should produce exactly the same results from each star.

The CREATE TABLE statement, shown in Figure 13-1, defines a new table in the database and prepares it to accept data. The various clauses of the statement specify the elements of the table definition. The syntax diagram for the statement appears complex because there are so many parts of the definition to be specified and so many options for each element. In addition, some of the options are available in some DBMS brands or in the SQL2 standard, but not in other brands. In practice, creating a new table is relatively straightforward.

Structural conformance can be controlled at design time, but the conformance of content must be enforced at load time One way to ensure consistent representation of data in the base and aggregate schema is to use the base star as the source for the aggregate data This option will be explored later in this chapter..

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4 discussed primary keys, foreign keys, and the parent/child relationships that they create between tables. Figure 11-1 shows the SALESREPS and OFFICES tables and illustrates once again how foreign keys and primary keys work. The OFFICE column is the primary key for the OFFICES table, and it uniquely identifies each row. The REP_OFFICE column, in the SALESREPS table, is a foreign key for the OFFICES table. It identifies the office where each salesperson is assigned.