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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. An alternative term for a data warehouse
Enterprise Information Management
Business Intelligence
Analytical applications
Constellation
2. Take data from a source system
Extract
Family
Star schema
Drilling down
3. Requesting information about related facts
Ad hoc query
Data mart bus architecture
Drilling across
Source system
4. Second stage of the data warehouse data architecture design process
Define the grain
Accessing
Snapshot
Operational BI
5. An operational system that provides data for a business information system
Dimensional modelling
ETL
Star schema
Source system
6. Data about the data
Production report
Dependent data mart
Metadata
Business Intelligence
7. A synonym for Business Intelligence
Independent data marts
Decision Support
Dimensional modelling
Enterprise Information Management
8. A visual display of the most important information needed by a particular user
Family
Design
Dashboard
Drilling across
9. Look-up tables referred to by fact tables
Dimension table
Transaction
Snapshot
Enterprise Information Management
10. Extract - Load and Transform
Operational BI
Translation table
ELT
Star schema
11. A simplified form of a data warehouse supporting the work of a single line of business
Data mart
Source system
Drilling across
Choose the dimensions
12. Splitting data tables into smaller tables for efficient access.
Transform
Partioning
Drilling down
Hub and spoke Architecture
13. Requesting more information about a particular fact
Drilling down
Aggregate tables
Transform
Data mart bus architecture
14. The level of detail required for a fact to be useful
Front end
Business Intelligence
Fact grain
Parallel partitioning
15. Fourth stage of building a data mart
ETL
Data mart bus architecture
Accessing
Star schema
16. simplest and least costly architecture developed to operate independently of each other - poor solution
Define the users
Construction
Population
Independent data marts
17. Fifth stage of building a data mart
Business query tool
OLAP
Maintenance
Dimensional modelling
18. A group of related fact tables
Partioning
Family
Operational system
Drilling down
19. Fourth stage of the data warehouse data architecture design process
Independent data mart
Current rolling snapshot
Define the users
Choose the facts
20. Draws data from operational or external systems
Master data
Drilling down
Independent data mart
Data mart bus architecture
21. A report created by an IT department user
Transaction
Production report
Back end
Analytical applications
22. A computer system used to support the day-to-day operations of an organisation
Constellation
Transaction
Operational system
Snapshot
23. Second stage of building a data mart
Construction
OLAP
Business Intelligence
Analytical applications
24. A single low-level fact representing a single business operation
Fact grain
Data mart bus architecture
Transaction
OLAP
25. A schema where dimensions are only connected to facts
Transaction
Fact table
Back end
Star schema
26. Extract - Transform and Load
Source system
Choose the facts
ETL
Current rolling snapshot
27. These extend BI into automating and optimising processes
Analytical applications
Transform
Production report
Master Data Management
28. First stage of building a data mart
Back end
Enterprise Information Management
Design
Transaction
29. Third stage of the data warehouse data architecture design process
Choose the dimensions
Master Data Management
Dashboard
Current rolling snapshot
30. Make changes to data so that it is compatible with a new database
Enterprise Information Management
Operational system
Transform
Fact grain
31. A table containing foreign keys and values
ELT
Fact table
Ad hoc query
Parallel partitioning
32. A schema where dimensions may be connected to facts or to other dimensions
Snowflake schema
Independent data mart
Snapshot
Current rolling snapshot
33. 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
Dimension table
Dimensional modelling
Choose the dimensions
34. A summary record for a specific reporting period
Fact grain
Snapshot
Maintenance
Design
35. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Translation table
Load
Data mart
Partioning
36. First stage of the data warehouse data architecture design process
Business query tool
Operational BI
Define the users
Production report
37. The operational systems - data warehouse and data marts
Decision Support
Snapshot
Back end
Partioning
38. Third stage of building a data mart
ELT
Population
Independent data marts
Aggregate tables
39. A query created by a BI user
Back end
Hub and spoke Architecture
Ad hoc query
Enterprise Information Management
40. Dimensions which are shared by two or more facts
Decision Support
Conformed dimensions
Data mart bus architecture
Snapshot
41. Unlike independent data marts the marts are linked via middleware
Business query tool
Data mart bus architecture
Family
Translation table
42. Used to support day-to-day operations
Drilling across
Family
Operational BI
ELT
43. A system that allows people to access and analyse data for business management and performance improvement
Choose the dimensions
Business Intelligence
Construction
Source system
44. 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
Data mart design
Aggregate tables
Fact table
Parallel processing and/or partitioning
45. The business applications
Master Data Management
Aggregate tables
Front end
Transform
46. Tables containing summary records calculated from the main fact tables
Dimension table
Aggregate tables
Ad hoc query
Define the users
47. Business applications - methods and tools that support the caputre and use of master data
Define the users
Accessing
Master Data Management
Independent data marts
48. A daily snapshot for each day of a set period
Drilling across
Snapshot
Independent data marts
Current rolling snapshot
49. Draws data from a data warehouse
Dependent data mart
Business Intelligence
Decision Support
Family
50. A logical design technique that presents data in a way that is optimised for high-performance access
Decision Support
Dimensional modelling
Choose the facts
Conformed dimensions