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