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