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4 years ago
Data Mining and Data Warehousing

Concept of combining the predictions made from multiple models of data mining and analyzing those predictions to formulate a new and previously unknown prediction.

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Rajiv Shah
Rajiv Shah
Sep 24, 2021
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2. Why Data Preprocessing is needed and which are the techniques used for data Preprocessing?

3. Explain Common Hadoop Shell Commands

4. What is Hadoop Architecture and Storage?

5. What is Big Data and Characteristics of Big Data V3s?

6. Explain Clustering, Spatial mining, Web mining, Text mining in brief

7. Explain usage of Data warehousing for information processing, analytical processing, and data Mining

8. What do you mean by data mart? What are the different types of data mart?

9. Explain meta data repository

10. Explain Data Warehouse Design Process in Detail

11. What is Data Warehouse? Explain it with Key Feature

12. What is Business Intelligence? Explain Business Intelligence in today’s perspective

13. How does the ANSI-SPARC architecture promote logical and physical data independence in databases?

14. What are the Major Issues and Challenges of Data Mining?

15. What is HOLAP?

16. What is Enterprise Warehouse?

17. What is Data Mart?

18. What are dependent and independent data marts?

19. What is Virtual Warehouse?

20. What is VLDB?

21. What are Research prototypes?

22. What is the difference between generic single-task tools and generic multi-task tools?

23. What are the areas in which data warehouses are used in present and in future?

24. What is DMQL?

25. What are the factors involved while choosing data mining system?

26. What is Text mining?

27. What is spatial data mining?

28. What are the DB Miner tool in data mining?

29. How data mining is used in health care analysis?

30. How data mining is used in banking industry?

31. Explain the types of data mining.

32. What does audio data mining mean?

33. What is OLAP?

34. What is OLTP?

35. Define Chameleon method?

36. What is CURE?

37. Differentiate Agglomerative and Divisive Hierarchical Clustering?

38. What is Hierarchical method?

39. What is CLARA and CLARANS?

40. What do u mean by partitioning method?

41. Define nominal, ordinal and ratio scaled variables?

42. Define Binary variables? And what are the two types of binary variables?

43. What are interval scaled variables?

44. What are the different types of data used for cluster analysis?

45. What are the requirements of cluster analysis?

46. What are the fields in which clustering techniques are used?

47. What is Clustering and Cluster Analysis?

48. What are the techniques to improve the efficiency of Apriori algorithm?

49. How to generate association rules from frequent item sets?

50. What is the purpose of Apriori Algorithm?

51. Describe the different classifications of Association rule mining.

52. Define support and confidence in Association rule mining.

53. How is a data warehouse different from a database?

54. Describe challenges to data mining regarding data mining methodology and user interaction issues.

55. Classifications of Data mining systems

56. What is Cluster Analysis?

57. What are the advanced database systems?

58. What is Descriptive model?

59. What is Predictive model?

60. What is the purpose of Data mining Technique?

61. What is Genetic algorithm?

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64. What is the Architecture of a typical data mining?

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