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