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