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