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