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