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