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