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