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