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