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