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