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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
Snowflake schema
Analytical applications
Population
Dashboard
2. Requesting information about related facts
Drilling across
Dimension table
Enterprise Information Management
ELT
3. Business applications - methods and tools that support the caputre and use of master data
Drilling down
Source system
Back end
Master Data Management
4. A daily snapshot for each day of a set period
Define the users
Current rolling snapshot
Parallel processing and/or partitioning
Population
5. Import data into a new database
Load
Data mart bus architecture
Independent data mart
Define the users
6. 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 across
Data mart bus architecture
Master data
7. A group of conformed dimensions
ETL
Snapshot
Partioning
Constellation
8. Draws data from operational or external systems
OLAP
Front end
Fact table
Independent data mart
9. A single low-level fact representing a single business operation
Construction
Define the grain
Operational BI
Transaction
10. A group of related fact tables
Choose the dimensions
Transaction
Dependent data mart
Family
11. Take data from a source system
Snowflake schema
Fact table
Extract
Metadata
12. Tables containing summary records calculated from the main fact tables
Aggregate tables
Current rolling snapshot
Decision Support
Master data
13. The level of detail required for a fact to be useful
Define the grain
Parallel partitioning
Dimension table
Fact grain
14. Splitting data tables into smaller tables for efficient access.
Data mart
Partioning
Design
Define the users
15. The business applications
Master Data Management
Business Intelligence
Conformed dimensions
Front end
16. A synonym for Business Intelligence
Data mart
Decision Support
Load
Current rolling snapshot
17. A schema where dimensions are only connected to facts
Constellation
Star schema
Enterprise Information Management
Ad hoc query
18. Fourth stage of the data warehouse data architecture design process
Choose the facts
Accessing
Independent data marts
Fact grain
19. A report created by an IT department user
Family
Star schema
Dependent data mart
Production report
20. A logical design technique that presents data in a way that is optimised for high-performance access
Partioning
Business Intelligence
Dimensional modelling
Transform
21. These extend BI into automating and optimising processes
Family
Construction
Analytical applications
Enterprise Information Management
22. Used to support day-to-day operations
Operational BI
Independent data mart
Drilling down
Front end
23. A summary record for a specific reporting period
Snapshot
Extract
Independent data mart
Back end
24. A system that allows people to access and analyse data for business management and performance improvement
Maintenance
Independent data mart
Business Intelligence
Hub and spoke Architecture
25. Second stage of building a data mart
Star schema
Transaction
ELT
Construction
26. Draws data from a data warehouse
Enterprise Information Management
Parallel partitioning
Dependent data mart
Drilling down
27. Extract - Transform and Load
Translation table
Business query tool
ETL
Design
28. Unlike independent data marts the marts are linked via middleware
Enterprise Information Management
Population
Data mart bus architecture
Current rolling snapshot
29. The operational systems - data warehouse and data marts
Operational BI
Business query tool
Back end
Dashboard
30. Allows multiple CPUs to process multiple queries simultaneously - providing scalability.
Independent data marts
Choose the facts
Parallel partitioning
Metadata
31. Data accessible to the whole data warehouse
Accessing
Partioning
Source system
Master data
32. Dimensions which are shared by two or more facts
Data mart design
Current rolling snapshot
Conformed dimensions
Business query tool
33. 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
Independent data mart
Data mart bus architecture
Operational system
34. A simplified form of a data warehouse supporting the work of a single line of business
Data mart
Business query tool
Aggregate tables
Partioning
35. First stage of building a data mart
Design
Data mart design
Production report
Decision Support
36. Look-up tables referred to by fact tables
Dashboard
Extract
Choose the dimensions
Dimension table
37. Online Analytical Processing
Translation table
Dimension table
OLAP
Source system
38. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Parallel processing and/or partitioning
Dashboard
Data mart bus architecture
Translation table
39. Data about the data
Constellation
Current rolling snapshot
Metadata
Fact table
40. A schema where dimensions may be connected to facts or to other dimensions
Snowflake schema
ETL
Enterprise Information Management
Current rolling snapshot
41. An alternative term for a data warehouse
Master Data Management
Enterprise Information Management
Accessing
Front end
42. A computer system used to support the day-to-day operations of an organisation
Metadata
Accessing
Transaction
Operational system
43. First stage of the data warehouse data architecture design process
Define the users
Operational system
Data mart design
Conformed dimensions
44. Extract - Load and Transform
ELT
Aggregate tables
Extract
Dashboard
45. Third stage of the data warehouse data architecture design process
Snapshot
Choose the dimensions
Business query tool
Transform
46. Fifth stage of building a data mart
Star schema
Metadata
Maintenance
Business Intelligence
47. Make changes to data so that it is compatible with a new database
Transform
Family
Construction
Independent data marts
48. 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
Dashboard
Snapshot
Parallel processing and/or partitioning
Current rolling snapshot
49. Requesting more information about a particular fact
Fact table
Decision Support
Drilling down
Front end
50. Second stage of the data warehouse data architecture design process
Define the grain
ELT
Construction
Conformed dimensions
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