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