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Oracle Data Warehousing 11g Essentials

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Answer 13 questions in 15 minutes.
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Match each statement with the correct term.
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1. List 5 high level Data Warehouse I/O considerations
Summary table - Aggregate table
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
Materialized views with aggregates - Materialized views with only joins - Nested materialized views
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

2. 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
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
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
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views

3. List 4 characteristics of a data warehouse as set forth by William Inmon
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
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
Statistical functions - OLAP - Data Mining

4. 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
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
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
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction

5. List two alternative names for Materialized Views in Data Warehousing theory
Summary table - Aggregate table
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
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
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views

6. What is a Data Warehouse?
Subject Oriented - Integrated - Nonvolatile - Time Variant
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
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
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

7. List Oracle Data Mining functions
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views
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
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction

8. List some physicla structures of a Data Warehouse
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
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views
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

9. Describe fact tables in a Data Warehouse
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
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.
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views
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

10. List the three types of materialized views
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
Materialized views with aggregates - Materialized views with only joins - Nested 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
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

11. List 3 ways (high level) to extract information from 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
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
Materialized views with aggregates - Materialized views with only joins - Nested materialized views

12. What is the main advantage in using ASM?
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
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
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction

13. What is a data mart?
Summary table - Aggregate table
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
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