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