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