- Type
- Quiz
- Course
- CS614 Data Warehousing
- Size
- PDF 1.8 MB
- Updated
- 23 Oct 2026
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- Online Extraction is a kind of -------------------- data extraction: Physical page 132 Logical Dimensional Multi valued
- The ---------------- saw the advent of disk storage, or DASD( direct Access Storage Device) : 1960s 1970s page 13 1950s 1990s
- Grain of a fact table means : The meaning of one fact table row page 109 The meaning of one dimensional table row Summary of aggregates in all fact tables Summary of aggregates in all dimension tables
- Normalization ----------------- : Reduces redundancy page 41 Increases redundancy Reduces joins Reduces tables
- Which of the following is not an example of a typical grain : Individual transaction Daily aggregates Monthly aggregates Normalized attributes page 111
- Multi-dimensional databases(MDDs) typically use -------------------- formats to store pre- summarized cube structures: SQL Proprietary file page 79 Object oriented Non-proprietary file
- ------------ provides a combination of “relational databases access” and “cube” data structures within a single framework: HOLAP page 78 DOLAP MOLAP ROLAP
- Data Warehouse provides the best support for analysis while OLAP carries out the ------------- task: Mandatory Whole Analysis page 69 Prediction
- ------------------ involves splitting a table by columns so that a group of columns is placed into the new table and the remaining columns are placed in another new table:
Adding redundant column
- OLAP implementations are highly/completely ------------------ : Normalized Demoralized page 69 Predictive Additive
- If each cell of Relation R contains a single value ( no repeating values) then it is confirmed that : Relation R is in 1st Normal Form page 43 Relation R is in 2nd Normal Form Relation R is in 3rd Normal Form Relation R is in 3rd Normal Form but not in 2nd Normal Form
- Which kind of relationships is captured by Fact less fact table: Many- to- Many page 121 One-to-many One-to-one
- Which of the following is not an example of dimension: Product
Region Sales volume page 78
- Which people criticize Dimensional Modeling (DM) as being a data mart oriented approach? Those that consider ER models as Data marts Those that consider Business processes as Data marts page 110 Those that consider Data marts as Data warehouse Those that consider dimensional model Those that consider dimensional modeling as de-normalization approach
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