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