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