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