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