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. Second stage of the data warehouse data architecture design process






2. 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)






3. Second stage of building a data mart






4. Third stage of building a data mart






5. Data about the data






6. A summary record for a specific reporting period






7. An alternative term for a data warehouse






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






9. Extract - Load and Transform






10. A schema where dimensions are only connected to facts






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






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






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






14. Fourth stage of building a data mart






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






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






17. 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






18. A query created by a BI user






19. Requesting information about related facts






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






21. Data accessible to the whole data warehouse






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






23. First stage of building a data mart






24. A group of conformed dimensions






25. Used to support day-to-day operations






26. These extend BI into automating and optimising processes






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. Requesting more information about a particular fact






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






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






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






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






33. Online Analytical Processing






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






35. The business applications






36. A report created by an IT department user






37. A table containing foreign keys and values






38. Draws data from operational or external systems






39. Import data into a new database






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






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






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






43. Take data from a source system






44. Fifth stage of building a data mart






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






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






47. The operational systems - data warehouse and data marts






48. Extract - Transform and Load






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






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