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