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