Define: Data Mart & Business Intelligence.
[3 marks]Perform feature wise comparison between OLAP & OLTP.
[4 marks]Draw and explain typical data mining architecture in detail with suitable diagram.
[7 marks]State the benefits of integrating Business intelligence with Data Warehousing.
[3 marks]State various data repositories on which data can be performed. Explain any one with example.
[4 marks]Explain three architecture of data warehouse with the help of neat diagram.
[7 marks]Explain major issues in data mining.
[7 marks]Define Support & Confidence.
[3 marks]Explain nominal and ordinal attribute types with suitable example.
[4 marks]Explain Bayesian classification with suitable example.
[7 marks]Define: Information gain and Tree Pruning.
[3 marks]What is a decision tree algorithm, and how does it work?
[4 marks]Find frequent itemset and generate strong association rules using Apriori algorithm for give transactional database. Consider minimum support = 2 is the occurrence of the items in the transactional datasets and minimum confidence is 75%. TID List of Items T1 A, C, D T2 B, C, E T3 A, B, C, E T4 B, E
[7 marks]Explain ETL process with suitable diagram.
[3 marks]Define clustering. What are the typical requirements of clustering in data mining.
[4 marks]Suppose that the data for analysis includes the attribute Marks as: 8, 10, 15 20. Use min-max normalization to transform the values for Marks onto the range [0:1].1
[7 marks]State various data transformation methods. Explain any one in detail.
[3 marks]Two stocks A & Bhaving values in one week as: - (2,5), (3,8), (5,10), (4,11), (6 14). It the stocks are affected by same industry trends; will their prices rise together or falls together. Prove using covariance analysis.
[4 marks]Suppose we want to investigate the relationship between the number of hours studied and the score obtained in a test. We collect data from 9 students and obtain the following results: Hours Studied Score250 Solve above data using linear regression to find the value of R-squared metric.
[7 marks]What is Neural Network. State their types.
[3 marks]Compare hierarchical and partitioning clustering.
[4 marks]Draw & explain HDFS architecture with suitable example.
[7 marks]Explain data mining application fraud detection with example.
[3 marks]What is Big data. State applications of big data.
[4 marks]Describe Hadoop architecture with suitable diagram.
[7 marks]