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