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