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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 visual display of the most important information needed by a particular user
Operational system
Dashboard
Partioning
Master Data Management
2. A daily snapshot for each day of a set period
Current rolling snapshot
Constellation
Hub and spoke Architecture
Accessing
3. Third stage of the data warehouse data architecture design process
Decision Support
Choose the dimensions
Transaction
Dashboard
4. Tables containing summary records calculated from the main fact tables
Aggregate tables
Back end
Translation table
Family
5. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Back end
Conformed dimensions
Constellation
Translation table
6. Third stage of building a data mart
Metadata
Transaction
Population
Production report
7. 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)
Drilling down
Dimensional modelling
Source system
Data mart design
8. Data about the data
Parallel processing and/or partitioning
Drilling down
Metadata
Drilling across
9. Allows multiple CPUs to process multiple queries simultaneously - providing scalability.
Independent data marts
Snowflake schema
Load
Parallel partitioning
10. Look-up tables referred to by fact tables
Dimension table
Snapshot
Hub and spoke Architecture
Source system
11. Extract - Transform and Load
Star schema
Snapshot
ELT
ETL
12. The level of detail required for a fact to be useful
Master data
Partioning
Family
Fact grain
13. Take data from a source system
Master data
Aggregate tables
Extract
Snowflake schema
14. Draws data from a data warehouse
Hub and spoke Architecture
Front end
Dependent data mart
Dimension table
15. Online Analytical Processing
Data mart design
Decision Support
Define the users
OLAP
16. Draws data from operational or external systems
Population
Independent data mart
Choose the dimensions
Data mart bus architecture
17. Extract - Load and Transform
Drilling down
Parallel processing and/or partitioning
ELT
Choose the facts
18. These extend BI into automating and optimising processes
Hub and spoke Architecture
Analytical applications
Data mart bus architecture
Dimensional modelling
19. Import data into a new database
Aggregate tables
Operational system
Construction
Load
20. A schema where dimensions may be connected to facts or to other dimensions
Operational system
Analytical applications
Design
Snowflake schema
21. Second stage of the data warehouse data architecture design process
Construction
Define the grain
Front end
Dimensional modelling
22. Requesting information about related facts
Maintenance
Hub and spoke Architecture
Family
Drilling across
23. The business applications
Choose the facts
Construction
Front end
Current rolling snapshot
24. An alternative term for a data warehouse
Enterprise Information Management
Transaction
Translation table
Data mart design
25. Data accessible to the whole data warehouse
Hub and spoke Architecture
Conformed dimensions
Master data
Transaction
26. Second stage of building a data mart
Constellation
Transform
Business Intelligence
Construction
27. 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
Fact grain
Dependent data mart
Data mart bus architecture
28. Used to support day-to-day operations
Operational BI
Conformed dimensions
Fact table
Dashboard
29. Unlike independent data marts the marts are linked via middleware
Drilling down
Define the users
Parallel partitioning
Data mart bus architecture
30. 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)
Fact table
Master data
Hub and spoke Architecture
Independent data marts
31. Fourth stage of building a data mart
Construction
Define the grain
Accessing
Metadata
32. A summary record for a specific reporting period
Front end
Parallel partitioning
Fact grain
Snapshot
33. Fourth stage of the data warehouse data architecture design process
Choose the facts
Choose the dimensions
Drilling down
Front end
34. A logical design technique that presents data in a way that is optimised for high-performance access
Design
Define the grain
Dimensional modelling
Business query tool
35. First stage of the data warehouse data architecture design process
Ad hoc query
Dependent data mart
Define the users
OLAP
36. A report created by an IT department user
Dimension table
Production report
Business Intelligence
Parallel processing and/or partitioning
37. A group of conformed dimensions
Data mart design
Constellation
Dashboard
Operational system
38. simplest and least costly architecture developed to operate independently of each other - poor solution
Independent data marts
Choose the dimensions
Decision Support
Aggregate tables
39. Make changes to data so that it is compatible with a new database
Ad hoc query
Transform
Conformed dimensions
Fact grain
40. A group of related fact tables
Define the users
Dashboard
Data mart design
Family
41. First stage of building a data mart
Current rolling snapshot
Family
Design
Transaction
42. The operational systems - data warehouse and data marts
Back end
Fact grain
Dimensional modelling
Choose the dimensions
43. A simplified form of a data warehouse supporting the work of a single line of business
Define the users
Transform
Data mart
Accessing
44. A table containing foreign keys and values
Drilling down
Population
Define the grain
Fact table
45. Dimensions which are shared by two or more facts
ELT
Ad hoc query
Conformed dimensions
Production report
46. Business applications - methods and tools that support the caputre and use of master data
Master Data Management
Data mart
Hub and spoke Architecture
Translation table
47. Splitting data tables into smaller tables for efficient access.
ELT
Parallel processing and/or partitioning
Fact table
Partioning
48. A system that allows people to access and analyse data for business management and performance improvement
Business Intelligence
Front end
Transaction
Master data
49. A computer system used to support the day-to-day operations of an organisation
Drilling down
Operational system
Operational BI
Dashboard
50. A single low-level fact representing a single business operation
Data mart
Transaction
Drilling down
Independent data mart