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