![]() For example, employees can be associated with orders for which they are responsible by creating a table relationship between the EmployeeID fields in the Employees and the Orders tables.ġ. In most cases, these matching fields are the primary key from one table, which provides a unique identifier for each record, and a foreign key in the other table. ![]() A table relationship works by matching data in key fields - often a field with the same name in both tables. This coordination is accomplished by using table relationships. ![]() ![]() In the preceding example, the fields in the tables must be coordinated so that they show information about the same order. These tables are linked to each other in a variety of ways to bring information from each into the form. The customer name in the Bill To box is retrieved from the Customers table, the Order ID and the Order Date values come from the Orders table, the Product name comes from the Products table, and the Unit Price and Quantity values come from the Order Details table. Information in this form comes from the Customers table. For example, the form shown here includes information drawn from several tables:ġ. You can then create queries, forms, and reports that display information from several tables at once. You do this by placing common fields in tables that are related, and by defining relationships between your tables. In this articleĪfter you have created a table for each subject in your database, you have to give Access a way to bring that information back together again when needed. To do this step correctly, though, you have to understand the relationships between your tables, and then specify these relationships in your database. You then provide Access with a way to bring the divided information back together - you do this by placing common fields in tables that are related. To achieve that goal, you divide your data into many subject-based tables so that each fact is represented only once. ![]() One of the goals of good database design is to remove data redundancy (duplicate data). ![]()
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