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