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