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Test your basic knowledge |
Data Warehousing
Start Test
Study First
Subject
:
it-skills
Instructions:
Answer 50 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
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. Used to support day-to-day operations
Operational BI
Constellation
Design
Independent data mart
2. Requesting information about related facts
Ad hoc query
Choose the dimensions
Drilling across
Data mart
3. An alternative term for a data warehouse
Drilling down
Enterprise Information Management
Metadata
Back end
4. A daily snapshot for each day of a set period
Operational BI
Data mart bus architecture
Snowflake schema
Current rolling snapshot
5. Fifth stage of building a data mart
Accessing
Source system
Define the users
Maintenance
6. A group of related fact tables
Business Intelligence
Dimensional modelling
Data mart design
Family
7. Draws data from a data warehouse
Design
Dependent data mart
Load
Choose the facts
8. A single low-level fact representing a single business operation
Transaction
Operational system
Data mart design
Snowflake schema
9. Fourth stage of building a data mart
Drilling across
Snowflake schema
Constellation
Accessing
10. Import data into a new database
Choose the dimensions
Decision Support
Source system
Load
11. Second stage of building a data mart
Back end
Aggregate tables
Construction
Population
12. Look-up tables referred to by fact tables
Business query tool
Construction
Dimension table
Aggregate tables
13. An operational system that provides data for a business information system
Parallel processing and/or partitioning
Metadata
Transaction
Source system
14. Extract - Transform and Load
Business Intelligence
Front end
ETL
Extract
15. Unlike independent data marts the marts are linked via middleware
Data mart bus architecture
Fact table
Define the grain
Independent data marts
16. Data about the data
Dependent data mart
Hub and spoke Architecture
ELT
Metadata
17. Business applications - methods and tools that support the caputre and use of master data
Master Data Management
Back end
Family
Dimension table
18. A group of conformed dimensions
ETL
Drilling down
Hub and spoke Architecture
Constellation
19. Tables containing summary records calculated from the main fact tables
Fact table
Front end
Aggregate tables
Choose the facts
20. The business applications
Construction
Operational BI
Front end
Data mart design
21. A logical design technique that presents data in a way that is optimised for high-performance access
Business query tool
Fact grain
Dimensional modelling
Maintenance
22. Fourth stage of the data warehouse data architecture design process
Operational system
Choose the facts
Translation table
ETL
23. Draws data from operational or external systems
Independent data mart
Production report
Operational BI
Accessing
24. A report created by an IT department user
Choose the facts
Production report
Business Intelligence
Design
25. simplest and least costly architecture developed to operate independently of each other - poor solution
Independent data marts
Independent data mart
Operational BI
Enterprise Information Management
26. A simplified form of a data warehouse supporting the work of a single line of business
Data mart
Ad hoc query
Maintenance
Constellation
27. The level of detail required for a fact to be useful
Maintenance
Fact grain
Extract
Data mart bus architecture
28. Take data from a source system
Star schema
Snapshot
Parallel partitioning
Extract
29. A table containing foreign keys and values
Choose the facts
Fact table
Constellation
Parallel partitioning
30. A synonym for Business Intelligence
Decision Support
Independent data marts
Master Data Management
Back end
31. The operational systems - data warehouse and data marts
Back end
Analytical applications
Dashboard
Business Intelligence
32. A query created by a BI user
Ad hoc query
Extract
Accessing
Population
33. Third stage of the data warehouse data architecture design process
Choose the dimensions
Current rolling snapshot
Dependent data mart
Drilling down
34. Requesting more information about a particular fact
Star schema
Drilling down
Choose the dimensions
Independent data mart
35. Extract - Load and Transform
ETL
ELT
Independent data marts
Define the users
36. A tool that allows users to write queries without having to learn SQL
Business Intelligence
Front end
Analytical applications
Business query tool
37. Splitting data tables into smaller tables for efficient access.
Ad hoc query
Partioning
Define the grain
Front end
38. A computer system used to support the day-to-day operations of an organisation
Enterprise Information Management
Analytical applications
Operational system
Conformed dimensions
39. All database architectural fall into one of these two categories: EDW or _________ (independent data marts - data mart bus architecture - hub and spoke architecture - centralized data warehouse - federated data warehouse)
Analytical applications
Fact table
Dashboard
Data mart design
40. A schema where dimensions are only connected to facts
Decision Support
Choose the dimensions
OLAP
Star schema
41. A visual display of the most important information needed by a particular user
Population
Production report
Dashboard
Source system
42. These extend BI into automating and optimising processes
Accessing
Ad hoc query
Snapshot
Analytical applications
43. First stage of building a data mart
Fact grain
Snowflake schema
Design
Fact table
44. A schema where dimensions may be connected to facts or to other dimensions
Choose the dimensions
Snowflake schema
Partioning
Operational BI
45. Make changes to data so that it is compatible with a new database
Transform
Drilling across
Define the grain
Back end
46. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Parallel partitioning
Operational BI
Population
Translation table
47. Data accessible to the whole data warehouse
Parallel partitioning
Ad hoc query
Master data
Family
48. Second stage of the data warehouse data architecture design process
Partioning
Define the grain
ETL
Parallel partitioning
49. First stage of the data warehouse data architecture design process
Construction
Fact grain
Dimension table
Define the users
50. Allows multiple CPUs to process multiple queries simultaneously - providing scalability.
Parallel partitioning
Star schema
Conformed dimensions
Enterprise Information Management