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