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