Meet Dr. Chitra Desai from Academia

At INSAID, we create accomplished and empowered Data Leaders. We groom our students to dominate the world of Data Science and Artificial Intelligence and reshape their future. We value what our students bring to the table. We share their vision and support them during their journey and ensure that they carve a niche for themselves.

We’re proud to have tutored exceptional students all across India. Today, one such exceptional student, Dr. Chitra Desai stands in the spotlight.

Student Name: Dr. Chitra Desai
Batch: GCDAI- February 2019
Total years of experience: 17 years
Area of expertise: Academics

INSAID Student Dr. Chitra DesaiMalvika: Hi Chitra, thank you for being here today. Can you start us off by walking us through your career journey?

Chitra: Yes sure. Basically, I started my career in 2000 after completing my NDA from Aurangabad. Thereafter, I decided to venture into teaching and keep on exploring new subjects.

Today I am at the position of a Professor and given my line of work, in 10 years, having reached this position is a strong achievement.

Malvika: Can you tell me what got you interested in Data Science and Artificial Intelligence in the first place?

Chitra: Data is giving rise to a new economy.

By 2020, we will generate about 44 trillion gigabytes of data.

Naturally, every business, be it a profit or nonprofit organization, wants to use data to improve on their system or services or product. Data Science equips them with better insights. Data is the place where you get solutions to most of the real-life problems. In every industry, for better performance or improvement of existing products and services, we’re looking at Data Science.

At the core of Data Science is machine learning. Big data, which recently came into the picture has given significant importance to machine learning. At the huge pace at which we’re generating data, it will become impossible for humans to analyze all of it. Machine learning picked momentum from 2010.

From a business context, it becomes Data Science and when it is applied to products, it is more of artificial intelligence.

Considering this relationship of machine learning with Data Science and artificial intelligence, I think that in everything starting from services to system improvements, including the product enhancements, artificial intelligence and data science are the undeniable future. This is why I wanted to be a part of this.

Malvika: What do you think is the goal of Data Science?

Chitra: Data comes in all forms- structured or unstructured. When we look at any data, we know it has a lot of hidden patterns. Based on these patterns, there are certain reasons why we assume a particular hypothesis is right or wrong.

Data will be used differently by different people; be it Software Engineers, Data Engineers, Data Analysts or a Digital Engineer.

So the common goal of Data Science would be to first understand what I need to gain from data, the first step of data literacy is to be able to explain and read data.

You have statistics to understand the numbers but you need Data Science to build a story around data. I need that story to be able to explain my findings to an audience and that I feel, is the goal of Data Science.

Malvika: Are there any current applications of Data Science and Artificial Intelligence that you’re interested in?

Chitra: Big companies with greater resources, like Google, are using Data Science and Artificial Intelligence to a greater extent whereas companies that are budding into the field of data science, are majorly dealing with analytics.

If I talk about application-oriented Artificial Intelligence, it’s the big companies that are contributing most and the newer ones are trying these products on an experimental basis.

The companies venturing into Data Science are grooming themselves; they are preparing for the next five years before getting to the adoption phase. Applications of Data Science are certainly seen in recommendation engines or forecasting mechanisms in statistics but that’s just the beginning.

Malvika: What are some initial challenges that you faced when you started in this industry? 

Chitra: I started in this field early last year and was researching a lot of trends and important takeaways. I attended a local session in Pune where people were discussing a lot of problems related to water distribution in Maharashtra.

Different politicians and social workers were discussing the huge amounts of data they had and each of them had a different point of view. The one thing that stood out in that discussion was that their data was not integrated. When it came to my turn to explain, I immediately pointed out that the interrelation of all this data was left out of the conversation.

From a technological standpoint, I explained that a huge amount of data related issues could be resolved if they had a working knowledge of machine learning to analyze back-end data. After my session at INSAID, I realized there is a need for structured learning and professional advice.

Malvika: Dr. Chitra, Do you have any Python packages or libraries that you like to use?

Chitra: I was new to Python when I started. At INSAID, I explored Numpy. I use Numpy when I need a simplistic view of things.

Before using something like Pandas, I want to find out more about the basic numbers; numerical data computation. I have worked on two projects using these packages and I can safely say they brought a lot of structure to my analysis.

Malvika: At INSAID, students are encouraged to build high-quality GitHub profiles. Have you built a GitHub portfolio and how do you think this will help you?

Chitra: I was not aware of GitHub profiles earlier. Now I feel that I have a repository for me to store everything in one place and also, anybody who wants to view or see what I’m working on, he has access to those resources.

Then people can also connect with me. Those working in my stream can always add some value to my existing projects.

Malvika: INSAID’s mission is to Groom Data leaders of tomorrow. What do you understand by a Data leader? And how is a Data leader different from a Data Scientist?

Chitra: Data Scientist is someone who takes all the inputs from a Software Engineer and Data Engineer and gets to analyzing all data.

When it comes to Data Leader, his objective would be to educate his team as a leader. He would expose his team to the importance and significance of data, he would see how the skill sets of his team can be optimally utilized and how the analytics derived can be best used to increase the efficiency of his organization.

Malvika: Thank You, Chitra! This has been very informative. On behalf of our team at INSAID, we wish you Good Luck for the future!

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