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