A Developers Guide To Data Modeling For Sql Server by Eric Johnson

By Eric Johnson

A Developer’s advisor to information Modeling for SQL Server explains the innovations and perform of knowledge modeling with a readability that makes the expertise available to somebody construction databases and data-driven applications.

“Eric Johnson and Joshua Jones mix a deep knowing of the technological know-how of knowledge modeling with the artwork that incorporates years of expertise. If you’re new to facts modeling, or locate the necessity to brush up on its strategies, this e-book is for you.”
Peter Varhol, government Editor, Redmond Magazine

Model SQL Server Databases That paintings greater, 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 standards. despite the fact that, 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 particular real-world strengths and weaknesses usually result in disastrous functionality.

A Developer’s consultant to info Modeling for SQL Server is a realistic, SQL Server-specific consultant to info modeling for each developer, architect, and administrator. This ebook provide you with helpful start-to-finish suggestions for designing new databases, remodeling latest SQL Server info versions, and migrating databases from different systems.

You’ll start with a concise, useful assessment of the middle information modeling strategies. subsequent, you’ll stroll via standards amassing and observe the best way to convert necessities into powerful 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 e-book allows you to

  • Understand your information model’s actual parts, from garage to referential integrity
  • Provide programmability through saved tactics, user-defined services, triggers, and .NET CLR integration
  • Normalize info versions, one step at a time
  • Gather and interpret requisites extra effectively
  • Learn an efficient technique for growing logical models
  • Overcome modeling difficulties with regards to entities, characteristic, information forms, garage overhead, functionality, and relationships
  • Create actual models—from constructing naming directions via enforcing enterprise principles and constraints
  • Use SQL Server’s specific indexing features, and triumph over their limitations
  • Create abstraction layers that improve defense, extensibility, and flexibility

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Additional resources for A Developers Guide To Data Modeling For Sql Server

Sample text

Experience tells us that things just don’t work that way: Technology is more successful when it’s deployed to solve a business problem. With data modeling, it’s easy to fall into implementing something that the business doesn’t need. To make your design work, you need to take a big step back and try to figure out what the business is trying to accomplish and then help it achieve its goals. You need to take the time to do data modeling correctly, and really dig into the company’s requirements. Later, we look specifically at how to get the requirements you need.

These two data types are designed to handle large amounts of character data in a single field. Again, as with the other character data types, the n prefix indicates whether or not the data is being stored in the Unicode format. Choose these data types when you will have very large amounts of alphanumeric text stored as a single attribute in an entity. Dates and Times Nearly every data model in existence requires that some entities have attributes that are related to dates and times. Date and time data can be used to track the time a change was made to an order, the hire date for employees, or even the delivery time for products.

Restrict: Checks data in the primary key value of the parent entity against the foreign key value of the child entity. If the value does not match, prevents the delete from taking place. Cascade: Deletes all matching entries from the child entity (in addition to the instance in the parent entity) based on the match of primary key value and foreign key value between the entities. Null (Set Null): Similar to Restrict; if the value does not match, sets the child foreign key value to NULL (or a specified default value) and permits the delete.

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