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