Test your basic knowledge |

Data Warehousing

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 single low-level fact representing a single business operation






2. Second stage of the data warehouse data architecture design process






3. 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






4. A database table that maps (e.g.) manufacturing product IDs to sales product IDs






5. Requesting more information about a particular fact






6. Fifth stage of building a data mart






7. A visual display of the most important information needed by a particular user






8. Fourth stage of building a data mart






9. Business applications - methods and tools that support the caputre and use of master data






10. Used to support day-to-day operations






11. Import data into a new database






12. First stage of building a data mart






13. The business applications






14. A report created by an IT department user






15. These extend BI into automating and optimising processes






16. A schema where dimensions may be connected to facts or to other dimensions






17. 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)






18. Look-up tables referred to by fact tables






19. A group of conformed dimensions






20. The operational systems - data warehouse and data marts






21. Tables containing summary records calculated from the main fact tables






22. Draws data from operational or external systems






23. Make changes to data so that it is compatible with a new database






24. A daily snapshot for each day of a set period






25. A simplified form of a data warehouse supporting the work of a single line of business






26. A computer system used to support the day-to-day operations of an organisation






27. 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)






28. Dimensions which are shared by two or more facts






29. Data about the data






30. simplest and least costly architecture developed to operate independently of each other - poor solution






31. Third stage of the data warehouse data architecture design process






32. A synonym for Business Intelligence






33. Splitting data tables into smaller tables for efficient access.






34. A system that allows people to access and analyse data for business management and performance improvement






35. A schema where dimensions are only connected to facts






36. Take data from a source system






37. An operational system that provides data for a business information system






38. Second stage of building a data mart






39. Fourth stage of the data warehouse data architecture design process






40. Requesting information about related facts






41. A tool that allows users to write queries without having to learn SQL






42. A query created by a BI user






43. The level of detail required for a fact to be useful






44. Unlike independent data marts the marts are linked via middleware






45. Data accessible to the whole data warehouse






46. Third stage of building a data mart






47. A logical design technique that presents data in a way that is optimised for high-performance access






48. An alternative term for a data warehouse






49. First stage of the data warehouse data architecture design process






50. Extract - Load and Transform