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Chapter 4 Tutorial. Modeling Data Warehouse A data warehouse is based on a multidimensional data model which views data in the form of a data cube A data.

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Presentation on theme: "Chapter 4 Tutorial. Modeling Data Warehouse A data warehouse is based on a multidimensional data model which views data in the form of a data cube A data."— Presentation transcript:

1 Chapter 4 Tutorial

2 Modeling Data Warehouse A data warehouse is based on a multidimensional data model which views data in the form of a data cube A data cube allows data to be modeled and viewed in multiple dimensions o Dimension tables o Fact table contains measures and keys to related dimension tables

3 Cont. 1.Star schema: A fact table in the middle connected to a set of dimension tables. 2.Snowflake schema: represents dimensional hierarchy by normalizing the dimension tables. save storage reduces the effectiveness of browsing 3.Fact constellations: Multiple fact tables share dimension tables

4 Q3 Suppose that a data warehouse consists of the three dimensions time, doctor, and patient, and the two measures count and charge, where charge is the fee that a doctor charges a patient for a visit. (a) Enumerate three classes of schemas that are popularly used for modeling data warehouses. 1.Star schema 2.Snowflake schema 3.Fact constellation schema

5 Q3 cont. (b) Draw a schema diagram for the above data warehouse using one of the schema classes listed in (a). Using a star schema.

6 Q3 cont. Star Schema time_key day day_of_the_week month quarter year time_key day day_of_the_week month quarter year time Fact Table Measures doctor_id doctor_name phone # address gender doctor_id doctor_name phone # address gender doctor patient_id patient_name phone # address gender patient_id patient_name phone # address gender patient time_key doctor_id patient_id Charge Count

7 Q5 Suppose that a data warehouse consists of the four dimensions, date, spectator, location, and game, and the two measures, count and charge, where charge is the fare that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. Draw a star schema diagram for the data warehouse.

8 Q5 cont. Star Schema date_id day month quarter year date_id day month quarter year date Sales Fact Table spectator_id spectator_name phone # address Status Charge rate spectator_id spectator_name phone # address Status Charge rate spectator game_id game_name description producer game_id game_name description producer game date_id spectator_id location_id game_id Charge Count location_id phone # Street city province country location_id phone # Street city province country location


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