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