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