By Eric Johnson
“ A Developer’s advisor to facts Modeling for SQL Server explains the ideas and perform of information modeling with a readability that makes the know-how available to someone construction databases and data-driven applications.
“Eric Johnson and Joshua Jones mix a deep figuring out 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 recommendations, 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 information modeling is key to making sure that your databases will practice good, scale good, and evolve to fulfill altering requisites. in spite of the fact that, if you’re modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic info modeling wisdom isn’t adequate: types that don’t mirror SQL Server’s special real-world strengths and weaknesses usually result in disastrous functionality.
A Developer’s advisor to facts Modeling for SQL Server is a realistic, SQL Server-specific advisor to information modeling for each developer, architect, and administrator. This ebook will give you beneficial start-to-finish counsel for designing new databases, remodeling latest SQL Server information types, and migrating databases from different structures.
You’ll commence with a concise, functional review of the center information modeling suggestions. subsequent, you’ll stroll via requisites accumulating and become aware of the right way to convert necessities into powerful SQL Server logical types. eventually, you’ll systematically remodel 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 spouse website.
This booklet allows you to
- Understand your facts model’s actual parts, from garage to referential integrity
- Provide programmability through saved tactics, user-defined capabilities, triggers, and .NET CLR integration
- Normalize information types, one step at a time
- Gather and interpret standards extra effectively
- Learn a good technique for growing logical models
- Overcome modeling difficulties concerning entities, characteristic, facts varieties, garage overhead, functionality, and relationships
- Create actual models—from developing naming guidance via enforcing company principles and constraints
- Use SQL Server’s detailed indexing functions, and conquer their limitations
- Create abstraction layers that improve protection, extensibility, and flexibility
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Additional info for A developer's guide to data modeling for SQL server : covering SQL server 2005 and 2008
Will a given table typically be written to or read from? Answering these questions goes a long way toward determining your indexes. We look at indexes and explore considerations for implementing them in Chapter 10, Indexing Considerations. Creating an Abstraction Layer Another important, and often overlooked, part of database design is the abstraction layer. An abstraction layer provides a level of access to the database without giving users direct access to the tables. To create an abstraction layer, you create views, stored procedures, and functions to access the data in the underlying tables.
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. 4 Schools and Deans entities, a one-to-many relationship 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.
Additionally, we look at a few things, such as subtype and supertype modeling, that aren’t necessarily problems but can be tricky. Building the Physical Model Once you have the logical model hammered out, you translate it into a physical model, and we turn to that topic in Part IV. A physical model is made up of the tables and other physical objects of your RDBMS. Much of the work of creating your database has been completed during the logical modeling, but that doesn’t mean you should take the physical model lightly.