Design a data warehouse for a regional weather bureau. The weather bureau has about 1,000 probes,...
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Design a data warehouse for a regional weather bureau. The weather bureau has about 1,000 probes, which are scattered throughout various land and ocean locations in the region to collect basic weather data, including air pressure, temperature, and precipitation at each hour. All data are sent to the central station, which has collected such data for over 10 years. Your design should facilitate efficient querying and on-line analytical processing, and derive general weather patterns in multidimensional space. Since the weather bureau has about 1,000 probes scattered throughout various land and ocean locations, we need to construct a spatial data warehouse so that a user can view weather patterns on a map by month, by region, and by different combinations of temperature and precipitation, and can dynamically drill down or roll up along any dimension to explore desired patterns. date dimension table time day month quarter year temperature dimension table temperature temp_range temp description weather fact table time region temperature precipitation region_map area region dimension table location id probe_location district city county region_name province precipitation dimension table precipitation prec_range prec_description Design a data warehouse for a regional weather bureau. The weather bureau has about 1,000 probes, which are scattered throughout various land and ocean locations in the region to collect basic weather data, including air pressure, temperature, and precipitation at each hour. All data are sent to the central station, which has collected such data for over 10 years. Your design should facilitate efficient querying and on-line analytical processing, and derive general weather patterns in multidimensional space. Since the weather bureau has about 1,000 probes scattered throughout various land and ocean locations, we need to construct a spatial data warehouse so that a user can view weather patterns on a map by month, by region, and by different combinations of temperature and precipitation, and can dynamically drill down or roll up along any dimension to explore desired patterns. date dimension table time day month quarter year temperature dimension table temperature temp_range temp description weather fact table time region temperature precipitation region_map area region dimension table location id probe_location district city county region_name province precipitation dimension table precipitation prec_range prec_description
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Related Book For
Business Statistics A Decision Making Approach
ISBN: 9780133021844
9th Edition
Authors: David F. Groebner, Patrick W. Shannon, Phillip C. Fry
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