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