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