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