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1 VALLIAMMAI ENGNIEERING COLLEGE SRM Nagar, Kattankulathur DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING Year & Semester : III & VI Section : CSE - 2 Subject Code : IT6702 Subject Name : Data warehousing and Data Mining Degree & Branch : B.E & CSE Staff in charge : Ms D.Kavitha S.No QUESTIONS COMPETENCE LEVEL UNIT -1 PART A 1. Describe sourcing, Acquisition and transformation tools? 2. Differentiate metadata and data mart Understand BTL-2 3. How would you classify the access tools? Analyze 4. How would you evaluate the goals of data mining? Evaluate BTL-5 5. Can you list the principles of data warehousing 6. What elements would you use to relate the design of data Apply warehouse? 7. Define Metadata? 8. Define Data partitioning? 9. Select the logical steps needed to build a data warehouse Evaluate BTL Define parallel RDBMS features? 11. Describe the alternate technologies used to improve the Understand BTL-2 performance in data warehouse environment? 12. Distinguish STARjoin and STARindex Understand BTL How would you show your understanding in Apply Multidimensional data model? 14. Formulate What conclusion can you draw in Bitmapped index 15. Explain Vendor solutions? Analyze 16. Explain the features of Metadata repository in data warehousing? Analyze
2 17. Define Metadata repository? 18. Discuss the main ideas in Prims solution Understand BTL How would you apply what you learned in Data warehousing? 20. How would you compare and substitute the ideas of potential performance problem with star schema? 1 i) Describe in detail about access tools types? ii) Describe the overall architecture of data warehouse? Apply Understand BTL-2 2 i)demonstrate in detail about Data marts Apply ii)demonstrate data warehouse administration and management 3 Explain the functional blocks needed to build a data Analyze warehouse? 4 Describe in detail about Mapping the Data warehouse to a multiprocessor architecture? 5 Analyze the information needed to support DBMS schemas Analyze for Decision support 6 Develop in detail about Vendor solutions? 7 i)discuss in detail about Vendor approaches Understand BTL-2 ii) Discuss in detail about access to legacy data 8 i) Describe in detail about data extraction? ii) Describe in detail about transformation tools? 9 How would you explain Metadata implementation with Evaluate BTL-5 examples? 10 Describe in detail about i) Bitmapped indexing ii)starjoin and index UNIT 2 PART A 1 Can you list the categories of tools 2 How would you describe the basic functions used in reporting tools? 3 Can you explain the tool to corporate data Analyze 4 Define the various access types to the data stored in a data warehouse? 5 What would demonstrate the result if an organization uses Apply a familiar approach to build a query and reporting environment for the data warehouse? 6 Summarize the approaches used in three tire client server Understand BTL-2 architecture 7 Explain the theme of SGF and DEF? Analyze 8 Compare ADF with SGF Analyze BTL4
3 9 Illustrate what changes would you make to solve the Apply problem in portability and supported platforms 10 Discuss the need for OLAP Understand BTL-2 11 How would you classify the ideas of multidimensional data Apply model with multirelational OLAP? 12 Which parameter and design choices determine the MOLAP? 13 Summarize to improve the purpose of ROLAP in OLAP Understand BTL-2 14 Define MQE? 15 Explain the difference between pilot software? Evaluate BTL-5 16 Generalize the function of OLAP tools in the internet 17 Describe MOLAP and ROLAP? Understand BTL-2 18 How would you explain the results for fusion components? Evaluate BTL-5 19 Describe the information needed to support the views of IBI FOCUS fusion? 20 List out the key features in business applications using OLAP? 1 i)how would you explain in detail about reporting query? Evaluate BTL-5 ii) Explain in detail about application of reporting query? 2 Compare in detail about tool categories in query tools Analyze 3 i) What is OLAP? Apply ii) How would you show your understanding about the need for OLAP? 4 Discuss in detail about the OLAP tools Understand BTL-2 5 Describe in detail about state of the market? 6 Examine the approaches used in i)multidimensional Apply ii)multirelational OLAP 7 Discuss in detail about the OLAP guidelines Understand BTL-2 8 Describe in detail about the applications of business analytics? 9 Examine in detail about various categories of OLAP tools? i) MOLAP ii) ROLAP iii) HOLAP 10 i)compose in detail about Cognous impromotu ii) Explain in detail about application in the internet? UNIT 3 Remember Remember BTL-1 BTL-1
4 PART A 1 Define Data mining? 2 List out the steps in data mining? 3 List the ways in which interesting patterns should be mined? 4 Compare drill down with roll up approach Analyze 5 Describe what are the other kinds of data? Understand BTL-2 6 How would you illustrate key distribution center? Apply 7 Analyze data characterization related to data discrimination Analyze 8 Define association and correlations? 9 List the essential ingredients of an attribute? 10 Evaluate the major tasks of data preprocessing Evaluate BTL-5 11 Discuss how would you categorize the requirements for Understand BTL-2 processing the data 12 Classify different types of reductions Apply 13 Distinguish between data cleaning and noisy data Understand BTL-2 14 Explain the principle elements of missing values in data Analyze cleaning? 15 Discuss the roles of noisy data in data preprocessing Analyze BTL-2 16 Can you develop the strategies in data reduction 17 Show how the attribute selection set is important in data Apply reduction 18 Evaluate when to use regression and log linear models Evaluate BTL-5 19 Formulate the ideas in correlation analysis 20 Define an efficient procedure for cleaning the noisy data? 1 i) Demonstrate in detail about data mining steps in the Apply process of knowledge discovery? ii) List the application area of data mining? 2 Explain in detail about data mining functionalities? Evaluate BTL-5 3 What approach would you designed to mine interestingness of patterns?
5 4 Distinguish various data mining task primitives? Understand BTL-2 5 Explain in detail about the classification of data mining Analyze systems? 6 i) Demonstrate in detail about integration of data mining Apply system with a data warehouse? ii) Illustrate the integration of data mining with warehouse with an example? 7 Describe in detail about data preprocessing? i) Data cleaning ii) Data Transformation iii) Data reduction 8 i)describe in detail about the issues of data mining ii) Describe in detail about the applications of data mining? 9 i)describe in detail about data integrity preprocessing ii) Describe in detail about reduction in data preprocessing? 10 i)discuss in detail about various data transformation Understand BTL-2 techniques ii)discuss in detail about and discretization techniques? UNIT-4 PART A 1 Define the Market basket analysis? 2 Formulate the principle frequent itemset and closed itemset 3 How would you explain the principle of Apriori algorithm? Evaluate BTL-5 4 Define Data pruning? 5 Compare join with prune step Analyze 6 Explain how will you generate association rules from Analyze frequent itemsets? 7 Compare hash based technique with transaction reduction Analyze 8 Discuss general road map on pattern mining Understand BTL-2 9 Describe the uses of multilevel mining with reduced Understand BTL-2 support? 10 Discuss the features of Decision tree induction Understand BTL-2 11 How would you evaluate attribute selection measures? Evaluate BTL-5 12 Define gain ratio and gain index? 13 Define Tree pruning? 14 Illustrate would result if a tree is not pruned Apply
6 15 How would you show your understanding about pessimistic Apply pruning? 16 Discuss decision tree induction? Understand BTL-2 17 What inference can you formulate with Bayes theorem? 18 Demonstrate the Bayes classification methods Apply 19 Define Lazy leaners? 20 Define state vector machine? 1 i)can you explain in detail about mining frequent pattern Analyze ii) Explain in detail about association and correlations? 2 i)how would you summarize in detail about mining methods? Understand BTL-2 ii)summarize in detail about various kinds of association rules 3 Describe in detail about what you learned to develop constraint and correlation based association mining? 4 What approach would you use to describe decision tree induction? 5 What are the features of Bayesian classification explain in Evaluate BTL-5 detail? 6 Analyze the function of support vector machine Analyze 7 Examine in detail about Lazy learners with examples? 8 Describe in detail about frequent pattern classification? Understand BTL-2 9 Demonstrate in detail about Back propagation Apply 10 i)can you formulate a theory for Bayes theorem ii)formulate rule based classification techniques UNIT 5 PART A 1 Identify what changes would you make to solve the problem in cluster analysis 2 Define K-means partitioning? 3 List the approaches in grid based methods? 4 Explain why a cluster has to be evaluated? Analyze 5 Illustrate the intrinsic methods in cluster analysis Apply 6 How do you explain the extrinsic and intrinsic methods? Evaluate BTL-5 7 Define biclustering?
7 8 How would you classify the difference between bicluster and Apply spectral clustering? 9 Classify what are the services provided by clustering graph and Apply network data 10 Formulate the role of application and challenges in clustering 11 Organize the design goals of graph clustering methods 12 Analyze categorization of constraints Analyze 13 Distinguish between hard constraints and soft constraints Understand BTL-2 14 Define outlier? 15 Discuss the challenges of outlier detection Understand BTL-2 16 Discuss the types of outlier Understand BTL-2 17 Evaluate what information is used by outlier detection method Evaluate BTL-5 18 Describe unsupervised method? Understand BTL-2 19 Define semi supervised method? 20 Explain the typical phases of outlier detection methods? Analyze 1 Based on what you know how will you explain cluster analysis Analyze 2 Describe in detail about categorization of major clustering methods? 3 Describe in detail about the features of K-means partioning method? 4 i) Explain in detail about hierarchical based method? Analyze ii)explain in detail about density based methods? 5 i)what is grid based method? ii) Examine in detail about proximity based approach? 6 Demonstrate in detail about model based clustering methods Apply 7 Describe in detail about clustering high dimensional data? Understand BTL-2 8 i)how would you discuss the outlier analysis Understand BTL-2 ii)discuss in detail about the various detection techniques in outlier 9 Will you explain in detail about data mining applications Evaluate BTL-5 10 Design statistical approaches in outlier detection with neat design and with examples
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