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Data Modeling and Analysis


In this chapter you will learn how to use a popular data-modeling tool, entity relationship diagrams, to document the data that must be captured and stored by a system, independently of showing how that data is or will be used—that is, independently of specific inputs, outputs, and processing. You will also learn about a data analysis technique called normalization that is used to ensure that a data model is a “good” data model. You will know data modeling and data analysis as systems analysis tools and techniques when you can:



Define systems modeling and differentiate between logical and physical system models.

Define data modeling and explain its benefits.

Recognize and understand the basic concepts and constructs of a data model.

Read and interpret an entity relationship data model.

Explain when data models are constructed during a project and where the models are stored.

Discover entities and relationships.

Construct an entity relationship context diagram.

Discover or invent keys for entities and construct a key-based diagram.

Construct a fully attributed entity relationship diagram and describe all data structures and attributes to the repository or encyclopedia.

Normalize a logical data model to remove impurities that can make a database unstable, inflexible, and nonscalable.

Describe a useful tool for mapping data requirements to business operating locations.





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