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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. First stage of the data warehouse data architecture design process
Define the users
Constellation
Construction
Family
2. Look-up tables referred to by fact tables
OLAP
Choose the dimensions
Dimension table
Operational system
3. Splitting data tables into smaller tables for efficient access.
Current rolling snapshot
Partioning
Dependent data mart
Extract
4. Requesting more information about a particular fact
Constellation
Current rolling snapshot
Enterprise Information Management
Drilling down
5. Fourth stage of building a data mart
Choose the facts
Accessing
Choose the dimensions
Conformed dimensions
6. A synonym for Business Intelligence
Fact table
Independent data marts
Decision Support
Operational system
7. Extract - Transform and Load
Front end
Translation table
Construction
ETL
8. Take data from a source system
Extract
ELT
Business Intelligence
OLAP
9. The level of detail required for a fact to be useful
Data mart bus architecture
Fact grain
OLAP
Data mart design
10. Tables containing summary records calculated from the main fact tables
Aggregate tables
Snapshot
Snowflake schema
Independent data marts
11. Data about the data
Independent data marts
Metadata
Load
Aggregate tables
12. Dimensions which are shared by two or more facts
Dependent data mart
Conformed dimensions
Dimensional modelling
Snapshot
13. An operational system that provides data for a business information system
Enterprise Information Management
Data mart bus architecture
Independent data marts
Source system
14. A simplified form of a data warehouse supporting the work of a single line of business
Data mart
Aggregate tables
Decision Support
Transaction
15. Third stage of the data warehouse data architecture design process
Enterprise Information Management
Choose the dimensions
Construction
Data mart
16. Allows multiple CPUs to process multiple queries simultaneously - providing scalability.
Parallel partitioning
Analytical applications
Dimensional modelling
Back end
17. A table containing foreign keys and values
Fact table
ETL
Front end
Transaction
18. Fifth stage of building a data mart
Hub and spoke Architecture
Transaction
Operational system
Maintenance
19. Make changes to data so that it is compatible with a new database
Transform
Dimensional modelling
Decision Support
Partioning
20. simplest and least costly architecture developed to operate independently of each other - poor solution
Constellation
Hub and spoke Architecture
Independent data marts
Operational system
21. Unlike independent data marts the marts are linked via middleware
Partioning
Business Intelligence
Front end
Data mart bus architecture
22. Draws data from operational or external systems
Business query tool
Define the grain
Parallel processing and/or partitioning
Independent data mart
23. Fourth stage of the data warehouse data architecture design process
Partioning
Choose the facts
Source system
Back end
24. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Back end
Master Data Management
Dashboard
Translation table
25. A tool that allows users to write queries without having to learn SQL
Business query tool
Drilling across
Front end
Conformed dimensions
26. Used to support day-to-day operations
Operational BI
Transform
Source system
Choose the facts
27. Second stage of building a data mart
Back end
Independent data mart
Construction
Drilling down
28. The business applications
Construction
Metadata
Front end
Dashboard
29. A computer system used to support the day-to-day operations of an organisation
Snapshot
Dimensional modelling
Data mart bus architecture
Operational system
30. Draws data from a data warehouse
Dependent data mart
Parallel processing and/or partitioning
Parallel partitioning
Data mart
31. Online Analytical Processing
ELT
Maintenance
OLAP
Decision Support
32. A single low-level fact representing a single business operation
Decision Support
Snowflake schema
Independent data marts
Transaction
33. A schema where dimensions are only connected to facts
Star schema
Snowflake schema
ETL
Enterprise Information Management
34. A group of related fact tables
Snowflake schema
Family
Ad hoc query
Define the grain
35. The operational systems - data warehouse and data marts
Back end
Constellation
Analytical applications
Population
36. A query created by a BI user
Snapshot
Aggregate tables
Master Data Management
Ad hoc query
37. Most famous data warehouse where a maintable infastructure includes a centralized data warehouse that serves for the needs of all organizational units (most favored 39 percent)
Hub and spoke Architecture
Data mart bus architecture
Transaction
Business query tool
38. A report created by an IT department user
OLAP
Choose the dimensions
Master data
Production report
39. Data accessible to the whole data warehouse
Master data
Front end
Business query tool
Ad hoc query
40. A group of conformed dimensions
Fact grain
Choose the dimensions
Constellation
Enterprise Information Management
41. 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)
Fact table
Enterprise Information Management
Parallel partitioning
Data mart design
42. Third stage of building a data mart
Population
Partioning
Parallel partitioning
Data mart design
43. Business applications - methods and tools that support the caputre and use of master data
Choose the dimensions
Maintenance
Family
Master Data Management
44. These extend BI into automating and optimising processes
Define the users
Choose the dimensions
Family
Analytical applications
45. A daily snapshot for each day of a set period
Dashboard
Current rolling snapshot
Dimension table
Parallel processing and/or partitioning
46. Requesting information about related facts
Business Intelligence
Data mart
Drilling across
Transform
47. Second stage of the data warehouse data architecture design process
Define the grain
Enterprise Information Management
Choose the facts
Data mart
48. First stage of building a data mart
ETL
Back end
Decision Support
Design
49. A schema where dimensions may be connected to facts or to other dimensions
Hub and spoke Architecture
Snowflake schema
Design
Maintenance
50. A logical design technique that presents data in a way that is optimised for high-performance access
Dimensional modelling
Data mart
Operational system
ELT