Big Data and Business Analytics


Event Name: Big Data and Business Analytics Event Date: 09-14 October 2023
Faculty Coordinators: Dr. Fehmina Khalique Event Timings:10:00 AM Onwards
Mode: Offline Number of Participants:50
Guest Speakers:Dr. Balamurugan Balusamy, Neha Issar, Neetu Kamra, Nallakaruppan and Others Venue: Lloyd Business School

Objectives

  • Business Intelligence Skills
  • Data-Driven Strategy Development
  • Hands-on Experience

 

Detailed Report

The 6-day FDP on Big Data and Business Analytics was conducted from 9 October to 14 October at Lloyd Business School. More than 50 participants nationwide participated, including guest speakers, professors, research scholars, and students. A brief report of the same is presented below: -

 

DAY 01: APPLICATION OF STATISTICS IN BUSINESS DECISION-MAKING & CREDIT RISK ASSESSMENT USING SPSS.

October 9, 2023, the workshop on Big Data & Business Analytics, a 6-day Faculty Development Program, started at Lloyd Business School. Dr. Fehmina Khalique (Professor LBS), the workshop convener, gave the program's opening comments and introduction to the workshop. Dr. Vandana Arora Sethi (Chief Strategy Officer, Lloyd Group of Institutions) presented the welcome address to the participants and guests. The Resource person, Dr. Balamurugan Balusamy, took the session on decision-making and discussed the importance of using data and statistics to make informed business decisions. He also took a session on credit risk assessment, which is a critical process for financial institutions that helps them make informed lending decisions. He emphasized that Predictive analytics, powered by tools like Microsoft Excel and VBA, can enhance the accuracy and efficiency

 

DAY 02: DBMS & RDBMS FOR FUNCTIONAL BUSINESS USING SSMS and DESCRIPTIVE ANALYTICS USING POWER BI.

The session started with a brief introduction by Ms. Neha Issar, IBM Spark & Scala Certified and Assistant Professor LBS, on the importance of DBMS & RDBMS and how it is used for functional business using SPSS. The next session started with a brief introduction of the topic by Dr Neetu Kamra, Head of the Centre of Data Analytics and AI Initiatives. She emphasized that Chatbot uses descriptive analysis through Power BI.

 

DAY 03: PREDICTIVE ANALYTICS USING SPSS MODELER

Ms. Rohini, the guest speaker (AI and Cloud Computing) from IBM, was the resource person for Day 3 on 11 October 2023. She explained how SPSS Modeler helps users build accurate predictive models quickly and deliver predictive intelligence to individuals, groups, systems, and enterprises. The different types of analytics i.e., Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics. She mainly focused on predictive analytics and how predictive analytics helps businesses and gave hands-on practice on SPSS Modeller to the participants.

 

DAY 04: DATA ANALYSIS USING PYTHON

Dr. Saurabh Agarwal. Dr Agarwal, a Professor of Machine Learning & Data Analytics from HBTU, Kanpur, was the Resource person for Day 04 on 12 October 2023. This FDP on Fundamentals of Python was organized to introduce the participants to the Python programming language and how data analysis is done with the help of Python. He also gave hands-on practice sessions to the participants. All participants had a learning experience.

 

DAY 05 & 06: INTRODUCTION TO BIG DATA, DEEP LEARNING, MACHINE LEARNING, ARTIFICIAL INTELLIGENCE & EXPLAINABLE AI.

Dr Nallakaruppan M.K Assistant Professor of IT& Engineering, Vellore Institute of Technology conducted a two-day workshop on Big Data, Deep Learning, Machine Learning, AI & Explainable AI on 13 and 14 October 2023. He also conducted practical experience on Orange Tool to handle and analyse data in analytics, mainly for predictive analysis and creating research models. On the last day of the FDP, a valedictory session was held for the resource persons and participants. Dr. Fehmina Khalique delivered the Vote of Thanks.

 

Learning Outcome

  • Participants gained hands-on experience with SPSS, including data entry, sorting, transformation, and conducting various statistical analyses such as descriptive statistics, correlation, and regression.
  • Attendees developed a deep understanding of bivariate analysis techniques, including exploratory data analysis, significance testing, hypothesis testing, and parametric testing using Python.

Participants acquired advanced skills in multivariate analysis using open-source R, including multiple regression, logistic regression, and other complex statistical techniques such as linear discriminant analysis and ordinal regression.