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