Data Modeler's Workbench: Tools and Techniques for Analysis by Steve Hoberman

By Steve Hoberman

This guide introduces 20 instruments for bettering the rate, accuracy, flexibility, and consistency of databases, information warehouses, and operational purposes. each one software is defined utilizing specific examples, its purposes are defined, and its optimum operational and reporting surroundings pointed out. specific cognizance is given to the system's beginning, the method of settling on its necessities, and the modeling of its requisites. Hoberman is a knowledge warehouse developer.

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Extra resources for Data Modeler's Workbench: Tools and Techniques for Analysis and Design

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The electrical contractors need to know many more details to help with the new wiring and connections to the existing wiring. This allows the architect to explain the requirements at different levels of detail, depending on the audience, just as the data model can be at subject area, logical, or physical level of detail. Senior management might just need to understand the subject area level of detail, whereas the functional team needs to understand the logical level and the technical team the physical level.

This technique of developing applications is based on the outputs of a high-level phase flowing into the inputs of a more detailed phase. For example, the business requirements phase flows into the functional requirements phase, which flows into the technical requirements phase, and so on, just like a waterfall. A waterfall gives us the picture in our minds of water flowing from a high to a low level. By picturing a waterfall, we can imagine the different software development phases flowing from one to the other.

The parrot joke is a great attention-getting device and helps us visualize his points clearly. Data Modeling Anecdotes In Practice To illustrate the steps to come up with a useful anecdote, I will go through an example of one that I use quite often. Let’s go through each of these three steps. Define Your Topic I wanted to explain why definitions were so important for the entities on a particular data model. This data model had many entities that had very encompassing and broad Team-LRN 8 CHAPTER 1 names, such as Business Party and Transaction.

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