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Oracle Data Warehousing 11g Essentials

Instructions:

Answer 13 questions in 15 minutes.
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Match each statement with the correct term.
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This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.

1. What is a Data Warehouse?
Statistical functions - OLAP - Data Mining
Fact tables are the large tables in your data warehouse schema that store business measurements. Fact tables typically contain facts and foreign keys to the dimension tables. Fact tables represent data - usually numeric and additive - that can be ana
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views
A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data - but can include data from other sources. Data warehouses sep

2. List 4 characteristics of a data warehouse as set forth by William Inmon
Fact tables are the large tables in your data warehouse schema that store business measurements. Fact tables typically contain facts and foreign keys to the dimension tables. Fact tables represent data - usually numeric and additive - that can be ana
Dimension tables - also known as lookup or reference tables - contain the relatively static data in the data warehouse. Dimension tables store the information you normally use to contain queries. Dimension tables are usually textual and descriptive a
The purpose of a materialized view is to increase query execution performance - The existence of a materialized view is transparent to SQL applications - A materialized view consumes storage space - The contents of the materialized view must be u
Subject Oriented - Integrated - Nonvolatile - Time Variant

3. Describe fact tables in a Data Warehouse
Subject Oriented - Integrated - Nonvolatile - Time Variant
Configure I/O for Bandwidth not Capacity - Stripe Far and Wide - Use Redundancy - Test the I/O System Before Building the Database - Plan for Growth
A data warehouse that is designed for a particular line of business - such as sales - marketing - or finance. In a dependent data mart - the data can be derived from an enterprise-wide data warehouse. In an independent data mart - data can be collect
Fact tables are the large tables in your data warehouse schema that store business measurements. Fact tables typically contain facts and foreign keys to the dimension tables. Fact tables represent data - usually numeric and additive - that can be ana

4. List 5 high level Data Warehouse I/O considerations
The purpose of a materialized view is to increase query execution performance - The existence of a materialized view is transparent to SQL applications - A materialized view consumes storage space - The contents of the materialized view must be u
Configure I/O for Bandwidth not Capacity - Stripe Far and Wide - Use Redundancy - Test the I/O System Before Building the Database - Plan for Growth
Subject Oriented - Integrated - Nonvolatile - Time Variant
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views

5. List 3 ways (high level) to extract information from a data warehouse
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views
Statistical functions - OLAP - Data Mining
Summary table - Aggregate table
Configure I/O for Bandwidth not Capacity - Stripe Far and Wide - Use Redundancy - Test the I/O System Before Building the Database - Plan for Growth

6. Describe dimension tables in a Data Warehouse
A data warehouse that is designed for a particular line of business - such as sales - marketing - or finance. In a dependent data mart - the data can be derived from an enterprise-wide data warehouse. In an independent data mart - data can be collect
Automatic Storage Management handles the tasks of striping and providing disk redundancy - including rebalancing the database files when new disks are added to the system.
Dimension tables - also known as lookup or reference tables - contain the relatively static data in the data warehouse. Dimension tables store the information you normally use to contain queries. Dimension tables are usually textual and descriptive a
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction

7. List two alternative names for Materialized Views in Data Warehousing theory
Automatic Storage Management handles the tasks of striping and providing disk redundancy - including rebalancing the database files when new disks are added to the system.
Configure I/O for Bandwidth not Capacity - Stripe Far and Wide - Use Redundancy - Test the I/O System Before Building the Database - Plan for Growth
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction
Summary table - Aggregate table

8. List some physicla structures of a Data Warehouse
Subject Oriented - Integrated - Nonvolatile - Time Variant
Automatic Storage Management handles the tasks of striping and providing disk redundancy - including rebalancing the database files when new disks are added to the system.
The purpose of a materialized view is to increase query execution performance - The existence of a materialized view is transparent to SQL applications - A materialized view consumes storage space - The contents of the materialized view must be u
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views

9. List Oracle Data Mining functions
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction
Fact tables are the large tables in your data warehouse schema that store business measurements. Fact tables typically contain facts and foreign keys to the dimension tables. Fact tables represent data - usually numeric and additive - that can be ana
Configure I/O for Bandwidth not Capacity - Stripe Far and Wide - Use Redundancy - Test the I/O System Before Building the Database - Plan for Growth
Statistical functions - OLAP - Data Mining

10. In what respects does a materialized view behaves like an index?
Dimension tables - also known as lookup or reference tables - contain the relatively static data in the data warehouse. Dimension tables store the information you normally use to contain queries. Dimension tables are usually textual and descriptive a
Summary table - Aggregate table
Subject Oriented - Integrated - Nonvolatile - Time Variant
The purpose of a materialized view is to increase query execution performance - The existence of a materialized view is transparent to SQL applications - A materialized view consumes storage space - The contents of the materialized view must be u

11. List the three types of materialized views
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction
Materialized views with aggregates - Materialized views with only joins - Nested materialized views
Subject Oriented - Integrated - Nonvolatile - Time Variant
The purpose of a materialized view is to increase query execution performance - The existence of a materialized view is transparent to SQL applications - A materialized view consumes storage space - The contents of the materialized view must be u

12. What is a data mart?
Automatic Storage Management handles the tasks of striping and providing disk redundancy - including rebalancing the database files when new disks are added to the system.
A data warehouse that is designed for a particular line of business - such as sales - marketing - or finance. In a dependent data mart - the data can be derived from an enterprise-wide data warehouse. In an independent data mart - data can be collect
Summary table - Aggregate table
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views

13. What is the main advantage in using ASM?
Statistical functions - OLAP - Data Mining
Automatic Storage Management handles the tasks of striping and providing disk redundancy - including rebalancing the database files when new disks are added to the system.
Materialized views with aggregates - Materialized views with only joins - Nested materialized views
Subject Oriented - Integrated - Nonvolatile - Time Variant