By Eric Johnson
Powerful facts modeling is vital to making sure that your databases will practice good, scale good, and evolve to satisfy altering specifications. despite the fact that, in case you are modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic info modeling wisdom is not sufficient: versions that do not mirror SQL Server's targeted real-world strengths and weaknesses usually bring about disastrous functionality.
Read Online or Download A Developer's Guide to Data Modeling for SQL Server: Covering SQL Server 2005 and 2008 PDF
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Extra resources for A Developer's Guide to Data Modeling for SQL Server: Covering SQL Server 2005 and 2008
To continue our Schools and Deans scenario, what if a university decides to implement a policy whereby each school has more than one dean? 4. info 38 Chapter 2 Elements Used in Logical Data Models You can see that there is a relationship between the entities such that you might have more than one dean for each school. This relationship is inherently scalable, because the separate entities can be updated and managed independently. Many-to-Many Relationships Of the logical relationships, many-to-many relationships, also called nonspecific relationships, are the most difficult concept, and possibly the most difficult to design.
1 Primary key and foreign key This example shows a basic relationship between two entities. After creating the relationship, you specify in its definition any constraints on data manipulation actions on the parent and child entities. For example, you can specify that any INSERT into the child entity should fail if there isn’t already a parent instance with a matching primary key value. info 34 Chapter 2 Elements Used in Logical Data Models fails unless all matching child entries are removed first.
Be wary of attaching attributes to one entity that actually belong to another entity. info Attributes 25 attributes in a logical model. For example, it is common for customer information to be physically stored with order information. This practice could lead to the belief that customer data, such as address or phone number, is an attribute of an order. However, customer is an entity in and of itself, as is an order. Storing the customer attributes with the order entity would complicate storage and data retrieval and possibly lead to a design that is difficult to scale.