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