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