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