By Eric Johnson

A Developer’s consultant to info Modeling for SQL Server explains the options and perform of knowledge modeling with a readability that makes the know-how obtainable to an individual construction databases and data-driven applications.

“Eric Johnson and Joshua Jones mix a deep knowing of the technology of knowledge modeling with the artwork that includes years of expertise. If you’re new to info modeling, or locate the necessity to brush up on its innovations, 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 vital 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 info modeling wisdom isn’t adequate: versions that don’t mirror SQL Server’s distinctive real-world strengths and weaknesses usually bring about disastrous functionality.

A Developer’s advisor to info Modeling for SQL Server is a realistic, SQL Server-specific advisor to facts modeling for each developer, architect, and administrator. This publication provides you with precious start-to-finish suggestions for designing new databases, remodeling latest SQL Server information types, and migrating databases from different systems.

You’ll start with a concise, functional review of the center information modeling options. subsequent, you’ll stroll via specifications collecting and notice tips to convert necessities into potent SQL Server logical versions. ultimately, you’ll systematically rework these logical versions into actual types 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 publication permits you to

  • Understand your information model’s actual components, from garage to referential integrity
  • Provide programmability through saved tactics, user-defined features, triggers, and .NET CLR integration
  • Normalize information versions, one step at a time
  • Gather and interpret requisites extra effectively
  • Learn a good technique for growing logical models
  • Overcome modeling difficulties relating to entities, characteristic, info kinds, garage overhead, functionality, and relationships
  • Create actual models—from developing naming instructions via imposing company ideas and constraints
  • Use SQL Server’s distinctive indexing services, and conquer their limitations
  • Create abstraction layers that increase defense, extensibility, and flexibility

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Extra info for A Developers Guide To Data Modeling For Sql Server

Example text

3, is not very scalable, and this is the kind of problem that can occur when you need to expand the model. 4. 4 An expanded customer model to include a separate address entity 10 Chapter 1 Data Modeling Overview As you can see, this model solves all our scalability problems. In fact, this new model doesn’t need to be scaled. We can still enter one address for each customer, but we can also easily enter more addresses when the need arises. Additionally, each address can be labeled so that we can tell what the address is for.

The application had to do many tricks in order to save and retrieve the data. This created far more work than would have been required in a well-designed system. Don’t get me wrong—I am not saying that all performance problems stem from bad design, but often bad design causes problems that can’t be corrected without a redesign. If the data model is sound from the get-go, you can focus your energy on actually tuning the database using indexes, statistics, or even access methods. Again, just like a house, a database that has a solid foundation lets you repair the problems that occur.

Decimals are numbers stored to the scale and precision specified. 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.

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