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Again, consider the example of our teacher work-flow application What if, instead of being designed for one school, the school board decides that this application should span all schools in the district so that it could centralize reporting and maintenance Suddenly, the model you were developing for 200 users at a school with 1,200 students may need to support 1,200 users managing records for 7,200 students Before, the response times were based on application servers in a school interacting with database servers in the same room Now, there may be application servers all over, or possibly at the central administration offices, and there may be only one database server to support them all However, the organization still expects the same response time even though the application (and database) will have to handle an increased load and latency You will need to compile and review this information during design to ensure that your model will scale well Do you need any additional entities or relationships Are there new attributes to existing entities And, when physically implemented, will your data model support the new requirements
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Gathering requirements is daunting and sometimes tedious, but it is a crucial step in the design phase of a functional data model The key is to gather as much data as possible; documents, screen captures, code, spreadsheets, interviews, observations, and use cases are all things you can use to figure out exactly what the new design will be Here we ve presented some techniques for gathering data In the next chapter, we look at how to take the volumes of data we ve gathered and turn it into requirements that will guide the design and development process for our fictitious company, Mountain View Music
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INTERPRETING REQUIREMENTS
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In 5, we looked at gathering the requirements of the business This process is similar to the process you go through whether you are building a house, developing an application, or trying to plan a birthday party Much of what we look at is theory and can be applied in any of these scenarios Sure, we looked at a few topics specific to database design, but the overall process is generic In this chapter, we get at the heart of database design; we look at how you begin to shape the business requirements into a database model, and eventually a physical database We also get into the specifics of our makebelieve customer, Mountain View Music, by taking a look at its requirements and exploring how to turn them into a model
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Mountain View Music
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Before we go further, let s get an overview of Mountain View Music It is important that you understand the company we will be working with and know how it is laid out; it will help you better understand the requirements as we talk about them Again, this is a company that we made up out of thin air We ve tried to keep the numbers and the details as realistic as possible In fact, at one point we both sat down and actually discussed the company s warehousing operation in detail We figured out the likely busy times and came up with a staffing schedule that would make sense to cover the shipment demand We wanted to figure out how big the company is to help us determine the transaction load to expect on the database The scenario is as real as we can make it; don t be surprised if we go into the Internet musical equipment business after this book is complete Mountain View Music was founded in 1991 in Manitou Springs, Colorado The founder, Bill Robertson, is a passionate music lover with a keen business sense All through high school and college he participated in 117
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