Evaluate the different clustering techniques, including K-means, hierarchical clustering and DBSCAN. Explain the underlying principles of each technique, and discuss their advantages, limitations, and practical applications.

Compare and contrast the various classification algorithms used in data mining, such as Decision Trees, Naive Bayes, Support Vector Machines, and Neural Networks. Discuss the strengths and weaknesses of each algorithm and provide examples of appropriate use cases for each.

Analyze various data pre-processing techniques such as data cleaning, data integration, data transformation, and data reduction. Explain the significance of each technique in improving the quality of data for mining and provide examples of scenarios where each technique would be applied.

Evaluate the role of data warehousing in supporting business intelligence and analytics. Discuss the process of transforming raw data into actionable insights. Provide examples of business intelligence tools and techniques that leverage data warehousing to enhance decision-making processes.

Explain the use of metadata in data warehousing. Discuss the different types of metadata and their roles. Provide examples of how metadata can enhance the usability, maintenance, and performance of a data warehouse.

Design a data warehouse schema for a retail company. Include fact tables, dimension tables, and consider the star schema and snowflake schema designs. Justify your design choices and discuss how your schema supports efficient query processing and business intelligence needs.

Analyze the concept of OLAP (Online Analytical Processing) and its significance in data warehousing. Describe the differences between MOLAP, ROLAP, and HOLAP. Discuss the advantages and disadvantages of each type with respect to data analysis and querying performance.

Explain the concept of Data Warehousing architecture. Compare and contrast the different types of architectures such as Single-tier, Two-tier, and Three-tier. Provide examples of scenarios where each architecture might be most beneficial.

Discuss the role of ETL (Extract, Transform, Load) processes in data warehousing. Provide a detailed explanation of each phase and its importance. Illustrate your answer with examples of common tools used in ETL and the challenges that may arise during these processes.

Write a program to create simple CRUD (Create, Read, Update, and Delete) application using Spring Boot and Hibernate for Online Registration and Fee Payment for a Workshop on “Web Technologies” to be organized by an IT Training Orgenization . Make provisions for security management in the program. Make necessary assumptions required.

Write a program using JSP and JDBC to support editing (address modification, mobile number/ email id update) of MCA 1st Semester students of IGNOU. The program should take enrollment number or registered mobile number as input. Make necessary assumptions required.

Draw Sequence Diagram for Online Shopping from an E-commerce Shopping Portal. Make necessary assumptions required.

Draw State Chart Diagram for Online Re-registration Fee Payment for IGNOU MCA 3 rd Semester. Make necessary assumptions required.

Draw Deployment Diagram for Online Banking System. Make necessary assumptions required

Draw Class Diagram for Online Examination System. Make necessary assumptions required.

Implement simple K-Means Algorithm to demonstrate the clustering rule on the following datasets:

(a) iris.arff 

(b) student.arff

Setup 4 nodes , two TCP client and server pair and two UDP client and server pair. Send packets to respective clients from both the servers. Monitor the traffic for both the pair and plot the number of bytes received. Make necessary assumptions.

Compute the Linear Discriminant projection for the following two-dimensional dataset

and

Consider the two-dimensional patterns (2, 2), (3, 6), (4, 4), (5, 6), (6, 7), (7, 8), (8, 8) and (9, 10). Using the PCA Algorithm, calculate the primary component.

Write Back Propagation algorithm, and showcase its execution on a neural network of your choice (make suitable assumptions if any)