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