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