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