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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. Online Analytical Processing
OLAP
Define the users
Family
Snowflake schema
2. Second stage of the data warehouse data architecture design process
Define the users
Define the grain
Operational system
Front end
3. Dimensions which are shared by two or more facts
Aggregate tables
Conformed dimensions
Dependent data mart
Define the users
4. Splitting data tables into smaller tables for efficient access.
Independent data marts
Dimensional modelling
Master Data Management
Partioning
5. Look-up tables referred to by fact tables
Source system
Aggregate tables
Choose the facts
Dimension table
6. Business applications - methods and tools that support the caputre and use of master data
Extract
Master Data Management
Star schema
Maintenance
7. A report created by an IT department user
Data mart bus architecture
Production report
Drilling across
Partioning
8. An alternative term for a data warehouse
Enterprise Information Management
Partioning
Snowflake schema
Fact table
9. Second stage of building a data mart
Ad hoc query
Analytical applications
Construction
Hub and spoke Architecture
10. Fourth stage of the data warehouse data architecture design process
Business query tool
Define the grain
Choose the facts
Fact table
11. Import data into a new database
Aggregate tables
Accessing
Load
Data mart bus architecture
12. A visual display of the most important information needed by a particular user
Transaction
Dashboard
Master Data Management
Dimension table
13. Used to support day-to-day operations
Operational BI
Design
Transform
Front end
14. A group of related fact tables
Family
Dashboard
Source system
Choose the dimensions
15. Data accessible to the whole data warehouse
Master data
Define the users
Independent data mart
Load
16. A database table that maps (e.g.) manufacturing product IDs to sales product IDs
Design
Load
OLAP
Translation table
17. The operational systems - data warehouse and data marts
Front end
Fact table
Back end
Define the users
18. 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)
Dimension table
Drilling across
Data mart design
Parallel processing and/or partitioning
19. Draws data from operational or external systems
Drilling down
Independent data mart
Production report
Parallel processing and/or partitioning
20. A summary record for a specific reporting period
Snapshot
Aggregate tables
Analytical applications
Operational BI
21. Fifth stage of building a data mart
Maintenance
Dimension table
Decision Support
Aggregate tables
22. Unlike independent data marts the marts are linked via middleware
Data mart bus architecture
ETL
Dimension table
Current rolling snapshot
23. A daily snapshot for each day of a set period
Choose the dimensions
Choose the facts
Current rolling snapshot
Master Data Management
24. Make changes to data so that it is compatible with a new database
Dimension table
Translation table
Conformed dimensions
Transform
25. Draws data from a data warehouse
Dimensional modelling
Snowflake schema
Load
Dependent data mart
26. First stage of building a data mart
Population
Metadata
Design
Data mart
27. Third stage of building a data mart
Transaction
Population
Independent data marts
Decision Support
28. These extend BI into automating and optimising processes
Data mart bus architecture
Analytical applications
Extract
Dashboard
29. A logical design technique that presents data in a way that is optimised for high-performance access
Construction
Source system
Metadata
Dimensional modelling
30. simplest and least costly architecture developed to operate independently of each other - poor solution
Snowflake schema
Independent data marts
Constellation
Dimensional modelling
31. Tables containing summary records calculated from the main fact tables
Star schema
Master data
Aggregate tables
Metadata
32. First stage of the data warehouse data architecture design process
Current rolling snapshot
Business Intelligence
Front end
Define the users
33. 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)
Constellation
Star schema
Analytical applications
Hub and spoke Architecture
34. A group of conformed dimensions
Parallel processing and/or partitioning
Drilling down
Constellation
Construction
35. A schema where dimensions are only connected to facts
Star schema
Extract
Drilling across
ELT
36. A table containing foreign keys and values
Source system
Fact table
Snapshot
Data mart
37. A schema where dimensions may be connected to facts or to other dimensions
Snowflake schema
Construction
Metadata
Hub and spoke Architecture
38. A computer system used to support the day-to-day operations of an organisation
Front end
Operational system
ETL
Constellation
39. 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
Operational system
Parallel processing and/or partitioning
Partioning
Constellation
40. Take data from a source system
Operational system
Extract
Accessing
Operational BI
41. Third stage of the data warehouse data architecture design process
Choose the facts
Ad hoc query
ELT
Choose the dimensions
42. Data about the data
Dependent data mart
Metadata
Parallel partitioning
Operational BI
43. Fourth stage of building a data mart
Accessing
Transaction
OLAP
Data mart
44. The business applications
Load
Front end
Current rolling snapshot
Choose the facts
45. A single low-level fact representing a single business operation
Star schema
Construction
Transaction
Operational BI
46. A synonym for Business Intelligence
Data mart bus architecture
Choose the dimensions
Analytical applications
Decision Support
47. Requesting more information about a particular fact
Drilling down
Construction
Define the grain
Parallel processing and/or partitioning
48. A query created by a BI user
Choose the dimensions
Production report
Aggregate tables
Ad hoc query
49. Extract - Transform and Load
ETL
Operational BI
Aggregate tables
Dimensional modelling
50. A system that allows people to access and analyse data for business management and performance improvement
Business query tool
Business Intelligence
Construction
Enterprise Information Management