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