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