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