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