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