Provide an example of a data warehouse model defining the grain, dimensions and facts of the data warehouse.
Part 2: 200-250 words with references
Identify the importance of selecting the Grain of a data warehouse in the Kimball Data Warehouse Model.  Provide examples of grains within a Data Warehouse.
Part 3: 200-250 words with references (2 paragraphs)
Describe one unique and specific example where you would use classification of type Decision Tree, Bayesian or Rule-Based and explain WHY. Use references and justification to support your point of view.

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