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