Engineering B.E. (Computer Engineering) Sem 8 Data Warehousing and Mining Dec 2019 Question Paper - Mumbai University | munotes
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Questions asked in this paper
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Q2 Answer any three out of remaining five questions
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Q3 Assume any suitable data wherever required and justify the same
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Q1 a) What is dimensional modeling? Design the data warehouse for wholesale furniture Company. The data warehouse has to allow to analyze the company’s situation at least with respect to the Furniture, Customer and Time. Moreover, the company needs to analyze: The furniture with respect to its type, category and material. The customer with respect to their spatial location, by considering at least cities, regions and states. The company is interested in learning the quantity, income and discount of its sales 10 marks
- b) i. Explain the architecture of data mining. 10
- ii. Explain different steps involved in data processing
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Q2 a) Differentiate top-down and bottom-up approaches for building data warehouse. Discuss the merits and limitations of each approach 10 marks
- b) Explain frequent pattern growth mining with example. 10
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Q3 a) For the following dataset, apply decision tree classification algorithm and show the Explain steps of ETL process in detail [10] Paper Subject Code: 52706 Data Warehouse and Mining 10 marks
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Q4 a) What is Clustering Techniques? Discuss the Agglomerative algorithm using following data and plot a Dendrogram using single link and link approach. The following figure contains sample data items indicting the distance between the elements: 10 marks
- b) i. Explain different OLAP models. 10
- ii. Differentiate Online transaction processing (OLTP) and Online: analytical
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Q5 a) Consider a data warehouse for a hospital where there are three dimension a) Doctor 10 marks
- b) Patient c) Time. Consider a measure charge fee that the doctor charges to a patient for a visit. Create a cube and illustrate the following OLAP operations:
- b) Discuss Association Rule Mining (AR) and Apriori Algorithm. Apply AR Mining to find all frequent item sets and association rules for the following dataset: 10
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Q6 Write short notes on any two of the following: 20 marks
- a) Linear Regression
- b) Data Visualization
- c) DBSCAN clustering
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