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. Draws data from operational or external systems






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






3. 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)






4. Allows multiple CPUs to process multiple queries simultaneously - providing scalability.






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






6. Second stage of building a data mart






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






8. Data accessible to the whole data warehouse






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






10. A query created by a BI user






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






12. 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






13. 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)






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






15. Take data from a source system






16. The operational systems - data warehouse and data marts






17. A summary record for a specific reporting period






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






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






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






21. Extract - Transform and Load






22. Requesting information about related facts






23. A single low-level fact representing a single business operation






24. The business applications






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






26. Dimensions which are shared by two or more facts






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






28. A schema where dimensions are only connected to facts






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






30. Draws data from a data warehouse






31. Fourth stage of building a data mart






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






33. Third stage of building a data mart






34. A table containing foreign keys and values






35. First stage of building a data mart






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






37. Look-up tables referred to by fact tables






38. Extract - Load and Transform






39. A group of related fact tables






40. An alternative term for a data warehouse






41. Data about the data






42. Requesting more information about a particular fact






43. Fifth stage of building a data mart






44. A synonym for Business Intelligence






45. Import data into a new database






46. Used to support day-to-day operations






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






48. A report created by an IT department user






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






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