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