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