By Eric Johnson
“ A Developer’s advisor to facts Modeling for SQL Server explains the thoughts and perform of information modeling with a readability that makes the expertise available to someone development databases and data-driven applications.
“Eric Johnson and Joshua Jones mix a deep knowing of the technology of knowledge modeling with the artwork that incorporates years of expertise. If you’re new to info modeling, or locate the necessity to brush up on its suggestions, this e-book is for you.”
—Peter Varhol, govt Editor, Redmond Magazine
Model SQL Server Databases That paintings higher, Do extra, and Evolve extra easily
Effective facts modeling is key to making sure that your databases will practice good, scale good, and evolve to fulfill altering necessities. although, if you’re modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic information modeling wisdom isn’t sufficient: versions that don’t mirror SQL Server’s specified 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 facts modeling for each developer, architect, and administrator. This ebook provide you with useful start-to-finish tips for designing new databases, remodeling present SQL Server facts versions, and migrating databases from different systems.
You’ll start with a concise, functional assessment of the center facts modeling options. subsequent, you’ll stroll via necessities accumulating and detect tips to convert specifications into potent SQL Server logical versions. ultimately, you’ll systematically rework these logical types into actual types that utilize SQL Server’s prolonged performance. All of this book’s many examples can be found for obtain from a better half site.
This booklet permits you to
- Understand your facts model’s actual components, from garage to referential integrity
- Provide programmability through kept strategies, user-defined features, triggers, and .NET CLR integration
- Normalize information versions, one step at a time
- Gather and interpret specifications extra effectively
- Learn an efficient technique for growing logical models
- Overcome modeling difficulties on the topic of entities, characteristic, information varieties, garage overhead, functionality, and relationships
- Create actual models—from developing naming directions via enforcing company ideas and constraints
- Use SQL Server’s distinctive indexing features, and conquer their limitations
- Create abstraction layers that improve safeguard, extensibility, and flexibility
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Extra resources for A developer's guide to data modeling for SQL server : covering SQL server 2005 and 2008
As with the alphanumeric data types, the specific information regarding the physical storage of these data types is covered in Chapter 3. Boolean Boolean data types are data types that evaluate to TRUE, FALSE, or NULL. This is a logic-based data type; although the data being stored may be Boolean, the actual data type is bit. A bit data type stores a 1 or a 0 or NULL. This translates to true, false, and nothing, respectively. Boolean data types are used for logic-based evaluation of data and are often used as switches or flags, such as a designator to describe whether a vehicle is in or out of service.
Scale in this case refers to the total number of numerals that are stored in the field, and precision refers to the number of those numerals stored to the right of the decimal point. Money is for the storage of currency and is accurate to different degrees based on the RDBMS being used. Float is an approximate number data type for use with floatingpoint data values. This is generally stored in scientific notation, and a designator can be specified with this data type that describes the number of bits that are used to store the number.
Status, Address, Phone Number, and Email are all examples of attributes that are likely to be identical in multiple entities. Rather than painstakingly create and maintain these attributes in each individual entity, you can use domains. A domain is a definition of an attribute that is maintained as part of the logical model but outside a given entity. Whenever an attribute that is part of a domain is used, that domain is added to the entity. Generally, a data model does not provide a visual indication that a given attribute is actually part of a domain.
A developer's guide to data modeling for SQL server : covering SQL server 2005 and 2008 by Eric Johnson