Title:     Department of Computer Science Report on Guest Lecture - “Introduction to Data Analytics”
Dates:    18/08/2023
Time:    10:00am onwards
Venue:   Sir M Visvesvaraya Auditorium
Resource Person:  Mr. Rajesh Harikrishnan, Ambassador – IICAIMA Biz Lab Certified Trainer, Lead in Analytics, Firebird Institute in Research Management, Coimbatore
Participants:  197 students
Coordinator:  Ms. Shilpa Nayak, Assistant Professor, Dept. of CS, MSRCASC

Objective of the Program:

To apply statistical analysis and technologies on data to find trends and solve problems.

A guest lecture on ‘Introduction to Data Analytics’ was organized by the Department of Computer Science, M S Ramaiah College of Arts, Science and Commerce on 18th Aug 2023 for the BCA and B.Sc students. The key speaker for the event was Mr. Rajesh Harikrishnan from Firebird Institute in Research Management, Coimbatore. Mr. Sharma has more than 15 years of Industry and teaching experience. His objective is to create a universal learning environment among students using Power Teaching Prototype and to inspire students to pursue global transformation and professional excellence in their career.

Mr. Rajesh Harikrishnan started the session with the definition of Big Data. “Big Data is an evolving term that describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information”. In simple words, Big Data is a pure technological term. He also added the general points by saying that-

• From the year 2014 DATA ANALYTICS had a huge growth.
• People started using data in all possible ways.
• Realtime data which means the data that is actively streaming.

He also discussed ‘Hadoop Analytics’. “Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs”. Also, he explained about different TYPES OF ANALYTICS :

• Descriptive analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics
• Cognitive analytics

(To handle the first 4 analytics we need a software or an algorithnm but the new analytic type i.e. cognitive is about the automation).

TYPES OF ANALYTICS IN USAGE LEVEL

• Adaptive
• Prescriptive
• Predictive
• Diagnostic
• Descriptive

The next topic that was continued was about the types of data and analytics in progress level.

TYPES OF DATA

• Structured
• Semi-structured
• Unstructured

Data analyst industry introduced 56 v’s of data, but where only 10 are important for one to remember and prepare for the interviews.

• Volume
• Value
• Velocity
• Veracity
• Viscocity
• Variability
• Volatality
• Viability
• Validity
• Variety

He also interacted with the students by asking questions on various real time examples of data analytics (case study).

BIG DATA EXAMPLES

• Rolls-royce
• BDO(banco de oro)
• Delta airlines
• Starbucks

There were few slides about the market basket analysis with some examples and pictures which was easy to grasp and understand.

Data analytics gives us much importance but the main thing is about the “CHALLENGES”.

Students have participated in large numbers in the guest lecture and they have not only seriously asked several questions but also gave their basic understanding and expressed their views

Students felt that the session was more informative and interactive. At the end of the guest lecture, students gave their feedback and explained how they were benifitted.

Outcome of the guest lecture:

• Formulate and use appropriate models of data analysis to solve hidden solutions to business-related challenges.
• Perform well in a group.
• Interpret data findings effectively to any audience, orally, visually, and in written formats.