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