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