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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. A group of related fact tables
Drilling down
Family
Data mart bus architecture
Population
2. Requesting more information about a particular fact
Drilling down
Master data
Data mart bus architecture
Snowflake schema
3. Second stage of building a data mart
Maintenance
Conformed dimensions
Construction
Independent data marts
4. A schema where dimensions are only connected to facts
Master data
Snapshot
Star schema
Transaction
5. A report created by an IT department user
Fact grain
OLAP
Transaction
Production report
6. Extract - Load and Transform
ELT
Front end
Data mart bus architecture
Drilling down
7. Second stage of the data warehouse data architecture design process
Business Intelligence
Decision Support
Define the grain
Translation table
8. Online Analytical Processing
Data mart bus architecture
OLAP
Aggregate tables
Operational system
9. Dimensions which are shared by two or more facts
Master data
Load
Conformed dimensions
Operational BI
10. The level of detail required for a fact to be useful
Source system
Fact grain
Dimension table
Partioning
11. 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)
Data mart design
Constellation
Metadata
ETL
12. A query created by a BI user
OLAP
Fact grain
Parallel processing and/or partitioning
Ad hoc query
13. Take data from a source system
Dependent data mart
Dimensional modelling
Extract
Enterprise Information Management
14. simplest and least costly architecture developed to operate independently of each other - poor solution
Transaction
Independent data marts
Operational BI
Back end
15. Third stage of building a data mart
Analytical applications
Snowflake schema
Drilling down
Population
16. A summary record for a specific reporting period
Design
Snapshot
Partioning
Define the grain
17. Data about the data
Metadata
Dashboard
Conformed dimensions
Partioning
18. Fifth stage of building a data mart
Maintenance
Front end
Parallel processing and/or partitioning
Data mart
19. These extend BI into automating and optimising processes
Back end
Population
Conformed dimensions
Analytical applications
20. A group of conformed dimensions
Dependent data mart
Analytical applications
Constellation
Dashboard
21. First stage of the data warehouse data architecture design process
Fact table
Define the users
Master data
Independent data mart
22. A visual display of the most important information needed by a particular user
Parallel processing and/or partitioning
Dashboard
Master data
Operational BI
23. An operational system that provides data for a business information system
Independent data marts
Constellation
Parallel partitioning
Source system
24. Third stage of the data warehouse data architecture design process
Choose the dimensions
Back end
Business Intelligence
Fact table
25. Issues to consider when deciding EDW architecture: 1. Which database management system (DBMS) should be used? (ex: Crash Data" MS SQL) 2. Will ______________________ be used? 3. Will data migration tools be used to load the data warehouse?4. What too
Design
Source system
Data mart design
Parallel processing and/or partitioning
26. Used to support day-to-day operations
Fact grain
Constellation
Operational BI
Parallel partitioning
27. Data accessible to the whole data warehouse
Current rolling snapshot
Choose the dimensions
Master data
Source system
28. Fourth stage of building a data mart
Data mart bus architecture
Accessing
Operational BI
Operational system
29. Extract - Transform and Load
Ad hoc query
Snowflake schema
ETL
Data mart design
30. A tool that allows users to write queries without having to learn SQL
Business query tool
Star schema
Parallel processing and/or partitioning
Metadata
31. The operational systems - data warehouse and data marts
Back end
Conformed dimensions
ETL
Snowflake schema
32. Requesting information about related facts
Drilling across
Choose the facts
Independent data mart
Operational BI
33. An alternative term for a data warehouse
Family
Enterprise Information Management
Operational BI
Hub and spoke Architecture
34. Draws data from operational or external systems
ELT
Business Intelligence
Independent data mart
Parallel partitioning
35. Tables containing summary records calculated from the main fact tables
Independent data mart
Aggregate tables
Decision Support
Population
36. A table containing foreign keys and values
Fact table
Choose the dimensions
Fact grain
Design
37. Splitting data tables into smaller tables for efficient access.
Production report
Partioning
Fact table
Parallel processing and/or partitioning
38. A logical design technique that presents data in a way that is optimised for high-performance access
Maintenance
Dimensional modelling
Translation table
Fact grain
39. A synonym for Business Intelligence
Fact table
Decision Support
ETL
Enterprise Information Management
40. Fourth stage of the data warehouse data architecture design process
Maintenance
Conformed dimensions
Choose the facts
Operational BI
41. Import data into a new database
Current rolling snapshot
Analytical applications
Load
Snapshot
42. A simplified form of a data warehouse supporting the work of a single line of business
Front end
Data mart
Ad hoc query
Dependent data mart
43. The business applications
Drilling down
Master data
Front end
Operational system
44. Unlike independent data marts the marts are linked via middleware
Data mart bus architecture
Hub and spoke Architecture
Define the grain
Accessing
45. Look-up tables referred to by fact tables
Dimension table
Transform
Family
Translation table
46. A computer system used to support the day-to-day operations of an organisation
Extract
Maintenance
Operational system
Business query tool
47. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Population
Translation table
Snowflake schema
Transform
48. A single low-level fact representing a single business operation
Snapshot
Transaction
Star schema
Front end
49. Make changes to data so that it is compatible with a new database
Back end
Ad hoc query
Transform
Decision Support
50. A schema where dimensions may be connected to facts or to other dimensions
Snowflake schema
Analytical applications
Dependent data mart
Constellation