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