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