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