A developer's guide to data modeling for SQL server : by Eric Johnson
By Eric Johnson
“ A Developer’s consultant to info Modeling for SQL Server explains the thoughts and perform of information modeling with a readability that makes the expertise obtainable to someone development databases and data-driven applications.
“Eric Johnson and Joshua Jones mix a deep realizing of the technology of knowledge modeling with the paintings that includes years of expertise. If you’re new to information modeling, or locate the necessity to brush up on its ideas, this e-book is for you.”
—Peter Varhol, government Editor, Redmond Magazine
Model SQL Server Databases That paintings higher, Do extra, and Evolve extra easily
Effective info modeling is vital to making sure that your databases will practice good, scale good, and evolve to fulfill altering necessities. in spite of the fact that, if you’re modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic facts modeling wisdom isn’t sufficient: versions that don’t mirror SQL Server’s detailed real-world strengths and weaknesses frequently bring about disastrous functionality.
A Developer’s consultant to facts Modeling for SQL Server is a realistic, SQL Server-specific consultant to info modeling for each developer, architect, and administrator. This booklet provides you with priceless start-to-finish advice for designing new databases, remodeling latest SQL Server info versions, and migrating databases from different structures.
You’ll commence with a concise, sensible evaluation of the center info modeling suggestions. subsequent, you’ll stroll via specifications accumulating and notice the best way to convert requisites into powerful SQL Server logical types. eventually, you’ll systematically rework these logical versions into actual versions that utilize SQL Server’s prolonged performance. All of this book’s many examples can be found for obtain from a significant other site.
This e-book allows you to
- Understand your facts model’s actual parts, from garage to referential integrity
- Provide programmability through kept techniques, user-defined features, triggers, and .NET CLR integration
- Normalize facts types, one step at a time
- Gather and interpret requisites extra effectively
- Learn an efficient technique for growing logical models
- Overcome modeling difficulties on the topic of entities, characteristic, information kinds, garage overhead, functionality, and relationships
- Create actual models—from constructing naming instructions via imposing enterprise ideas and constraints
- Use SQL Server’s specified indexing services, and triumph over their limitations
- Create abstraction layers that improve safety, extensibility, and flexibility
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Sample text
Relationship Types Logically, there are three distinct types of relationships between entities: one-to-one, one-to-many, and many-to-many. Each represents the way two entities logically relate to each other. It is important to remember that these relationships are logical; physical implementation is another step, as discussed later in Chapter 9. One-to-One Relationships Simply put, a one-to-one relationship between two entities is, as the name implies, a direct match between the entities. For each record in the first entity, there is one matching record in the second entity, no more and no less.
Cardinality In every relationship we’ve discussed, we’ve specified only the general type of relationship—one-to-one, one-to-many, and many-to-many. In each case, the description of the relationship is a specification of the number of records in a parent entity in relation to the number of records in a child entity. To more clearly model the actual relation of the data, you can be more specific when defining these relationships. What you are specifying is the cardinality of the relationship. With a one-to-one relationship, the cardinality is implied.
For example, you can use the Deans_Schools entity to note how long a specific dean has been in charge of a given school. If you have multiple combinations, the 40 Chapter 2 Elements Used in Logical Data Models length of tenure for a dean at a given school may vary, so this attribute could be very useful. Many-to-many relationships are widely used, but you should approach them with caution and carefully document them to ensure that there is no confusion as you move forward with the physical implementation.