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