Including association rule mining and network analysis

Department of Computing CS-404 Big Data Analytics Class: BESE-11 & BSCS-11
Spring 2024

Lab Manual 09: Open Ended Lab
Date: 16-04-2024
Time: 10:00-12:50 & 14:00-16:50
Instructor: Dr. Syed Imran Ali & Dr. Muhammad Daud Abdullah Asif
Lab Engineer: Engr. Masabah Bint E Islam

• Implementation of Data Analysis Techniques: Apply at least two different techniques, such as association rule mining and other methods studied in class, to analyze the data comprehensively.

• Interpretation and Application: Use the results of your data analysis to address specific research questions or business problems. Interpret the data to provide actionable insights.

Task 1: Business Context and Background:
• Students are required to select a dataset of their choice from platforms such as Kaggle.com and Data.world. The dataset should contain more than 10 columns with a mix of quantitative and qualitative variables and should consist of at least 1000 rows of data.

• Provide an overview of the business context related to the chosen dataset and discuss relevance of the dataset to real-world applications. Describe any industry or domain-specific insights that can be derived from the dataset.

• Report on the relationships between variables as they relate to the respective research questions.

Task 4 - Research Questions:

categorical or discretised numerical data.

• Enhance data quality for analysis by removing outliers and performing necessary cleaning.

Task 6- Interpretation

of Rules:

• Discuss any limitations of the technique in the context of the specific dataset and use case.