Q. In a factless fact table representing student attendance, what value is typically recorded in each row to indicate attendance?

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Q. What is one advantage of keeping the fact table at the lowest granularity level?

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Q. What are the natural lowest levels of dimensions in a fact table?

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Q. How do granular fact tables facilitate "graceful" changes to data models?

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Q. Why do data warehouses feed data into data mining applications?

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Q. In a dimension table, what is the primary key used for?

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Q. What issues can arise when using operational system keys as primary keys for dimension tables?

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Q. What is the first principle to consider when choosing primary keys for dimension tables?

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Q. What are surrogate keys in dimension tables?

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Q. How are operational system keys typically handled in dimension tables when surrogate keys are used?

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Q. Why do dimension tables often use surrogate keys?

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Q. In a STAR schema, why must the primary key of each dimension table also be a foreign key in the fact table?

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Q. Which option is commonly used for defining primary keys in a STAR schema fact table?

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Q. What is the fundamental difference between the STAR schema and relational schemas for OLTP systems?

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Q. When might a denormalized dimension table not be desirable in a STAR schema?

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Q. What is one of the key advantages of the STAR schema for data warehousing?

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Q. In the context of a STAR schema, what does "denormalized" refer to?

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Q. In a data warehouse, what distinguishes users of decision support systems, such as data warehouses, from users of OLTP systems?

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Q. How does the STAR schema differ from the relational schema of an OLTP system in terms of user-friendliness?

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Q. Why is the STAR schema considered to be intuitively understood by users?

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