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