CH 8 430
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