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