You can just show table listings in your solution document. Your sample rows should include all...
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You can just show table listings in your solution document. Your sample rows should include all revenue events in the range from February 10, 2020, to February 21, 2020. 1. You should identify dimensions, map dimensions to data sources, and specify dimension hierarchies. For each dimension, you should identify its data sources and attributes in each data source. For hierarchical indicate the levels from broad to narrow. only, do mensions, you should 2. You should specify measures, related data sources, and measure aggregation properties. z@csuglobal.c 3. Identify the grain in your dimensional design using the business needs as a guideline. You should then indicate relative storage requirements for the grain using statistics for the data sources. Using the cardinality estimates provided, you should determine either the fact table size or sparsity and then compute the unknown grain size variable. For example, you should compute sparsity if the fact table size is given. only, do not re 4. Extend your analysis to design a star schema (or variation) to support inventory analysis. For each table, you should define the table name, primary key, and 23-12-19 design transformations, especially the flatten and merge transformations where appropriate. You can just show table listings in your solution document. Your sample rows should include all revenue events in the range from February 10, 2020, to February 21, 2020. 1. You should identify dimensions, map dimensions to data sources, and specify dimension hierarchies. For each dimension, you should identify its data sources and attributes in each data source. For hierarchical indicate the levels from broad to narrow. only, do mensions, you should 2. You should specify measures, related data sources, and measure aggregation properties. z@csuglobal.c 3. Identify the grain in your dimensional design using the business needs as a guideline. You should then indicate relative storage requirements for the grain using statistics for the data sources. Using the cardinality estimates provided, you should determine either the fact table size or sparsity and then compute the unknown grain size variable. For example, you should compute sparsity if the fact table size is given. only, do not re 4. Extend your analysis to design a star schema (or variation) to support inventory analysis. For each table, you should define the table name, primary key, and 23-12-19 design transformations, especially the flatten and merge transformations where appropriate.
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Related Book For
Data Modeling and Database Design
ISBN: 978-1285085258
2nd edition
Authors: Narayan S. Umanath, Richard W. Scammel
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