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Confirming PagesChapter3 The Software Process Learning Objectives After studying this chapter, you should be able to Explain why two-dimensional lifecycle models are important. Describe the five core.
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Workflows FAQ
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Definition(s): Framework of processes and activities concerned with the life cycle that may be organized into stages, which also acts as a common reference for communication and understanding.
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Dimensional models are more denormalized and optimized for data querying, while normalized models seek to eliminate data redundancies and are optimized for transaction loading and updating.
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Data Dimensional Modelling (DDM) is a technique that uses Dimensions and Facts to store the data in a Data Warehouse efficiently. It optimises the database for faster retrieval of the data. Dimensional Models have a specific structure and organise the data to generate reports that improve performance.
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The life cycle of a dimensional model includes design, test, transform, and production phases.
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The four key decisions made during the design of a dimensional model include: Select the business process. Declare the grain. Identify the dimensions. Identify the facts.
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Dimensional Data Modeling is used for calculating summarized data. For example, sales data could be collected on a daily basis and then be aggregated to the week level, the week data could be aggregated to the month level, and so on. The data can then be referred to as aggregate data.
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