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