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