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