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