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