CH 8 430

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Independent data marts approach can be used for designing an enterprise-wide analytical data warehouse.

FALSE

Normalized data warehouse approach results in multiple unrelated ETL infrastructures.

FALSE

The ER modeling and dimensional modeling methods cannot be combined and used within the same data warehousing project.

FALSE

The relational model is the only way through which dimensionally modeled databases can be implemented.

FALSE

When a data warehouse is normalized, its dependent data marts also must be normalized.

FALSE

A dimensional model cannot be based on a single source.

FALSE

Aggregated fact tables have a finer level of granularity than detailed tables.

FALSE

All sources for a dimensional model must be operational data sources from the company that is building the dimensional model

FALSE

Dimensionally modeled data warehouse approach results in multiple unrelated ETL infrastructures.

FALSE

A dimensional model can contain more than one fact table.

TRUE

Analytical queries on the dimensionally modeled database can be significantly simpler to create than on the equivalent nondimensional database.

TRUE

Dimensional modeling can be employed as a relational data modeling technique.

TRUE

Dimensionally modeled data warehouse approach can be used for designing an enterprise-wide analytical data warehouse.

TRUE

Independent data marts approach results in multiple unrelated ETL infrastructures.

TRUE

Normalized data warehouse approach can be used for designing an enterprise-wide analytical data warehouse.

TRUE

In addition to giving each record of a dimension a new value that serves as a primary key within the dimensional model instead of the operational key value, surrogate key values contain additional information about each record in the dimension.

FALSE

Transaction time is typically included as a column in the fact table.

TRUE


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