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