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