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