A Developer's Guide to Data Modeling for SQL Server: by Eric Johnson

By Eric Johnson

Potent facts modeling is key to making sure that your databases will practice good, scale good, and evolve to satisfy altering necessities. in spite of the fact that, if you are modeling databases to run on Microsoft SQL Server 2008 or 2005, theoretical or platform-agnostic info modeling wisdom isn't really adequate: types that do not replicate SQL Server's specified real-world strengths and weaknesses usually bring about disastrous functionality.

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Next, we discuss the business review of the model. It’s crucial to get your customers’ buy in and sign-off of the logical model. Once the customer has approved the model, you can document releases and work toward the agreed-upon system. We cannot reiterate this point enough: You cannot skip this step. It will save you days of pain down the line if the company needs to make changes to the requirements. If you have agreed-upon release cycles, then you can simply add new changes at the expense of the project’s time line or of other requirements.

The Process of Data Modeling This book is written as a step-by-step, process-oriented look at data modeling. You will walk through a real-world project from start to finish. Your journey will follow Mountain View Music, a fictitious small online music retailer that is in the process of redesigning its current system. You will start with a little theory and work toward the final implementation of the new database on Microsoft SQL Server 2008. The main topic of this book is not data modeling theory, but we give you enough information on theory to start constructing a sound model.

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. For now, just keep in mind that if you do your job as a data modeler correctly, you will meet the needs, and not only the wants, of your customer. Easy Data Retrieval Once you have data stored in a database, it is useful only if users can retrieve it.

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