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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 4 characteristics of a data warehouse as set forth by William Inmon
Subject Oriented - Integrated - Nonvolatile - Time Variant
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
Statistical functions - OLAP - Data Mining

2. List Oracle Data Mining functions
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
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

3. List some physicla structures of 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
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
Materialized views with aggregates - Materialized views with only joins - Nested materialized views

4. In what respects does a materialized view behaves like an index?
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
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

5. Describe dimension tables in a Data Warehouse
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
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
Statistical functions - OLAP - Data Mining

6. List 3 ways (high level) to extract information from 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.
Statistical functions - OLAP - Data Mining
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

7. Describe fact tables in a Data Warehouse
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 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
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

8. What is the main advantage in using ASM?
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
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

9. List 5 high level Data Warehouse I/O considerations
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
Materialized views with aggregates - Materialized views with only joins - Nested materialized views
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views

10. What is a data mart?
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
Summary table - Aggregate table
Classification - Regression - Anomaly Detection - Attribute Importance - Clustering - Associations - Feature Extraction

11. List the three types of materialized views
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
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
Summary table - Aggregate table

12. What is a Data Warehouse?
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 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
Tablespaces - Tables and Partitioned Tables - Views - Integrity Constraints - Dimensions - Indexes and Partitioned Indexes - Materialized Views
Statistical functions - OLAP - Data Mining

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