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INSAID is proud to mentor students who demonstrate distinctive & outstanding qualities, developing them into passionate Data Leaders. We’re an integral part of their learning journey and help them overcome hurdles and celebrate achievements. After all, we have to guide them to reach the pinnacle of their career.

Today, we bring to you a conversation with one of our new students, an excited and driven learner Arijit Chakrabarti who is enrolled in our flagship program – Global Certificate of Data Science. Let us hear from him; what draws him to Data Science and how he developed as a data enthusiast notwithstanding his non-programming background. 

Malvika: Arijit, Could you walk me through your professional experience?

Arijit: I am a Delhi University second rank holder in English literature (BA Hons.) post which I pursued a Postgraduate Diploma in Advertising and Communications Management from Symbiosis Institute of Business Management, Pune. I excelled in my batch at SIBM and started my career with Times of India in Corporate Strategy reporting to the Vice Chairman and Board of Directors. The role was intense and required me to collaborate across diverse departments as I acted in the role of an internal consultant for the organsation. 

In my subsequent roles strategy gradually became my prime area of competence. During my experience of 18+ years I have worked with leading brands like DDB Mudra, Greenlam Industries Ltd., Madison OOH, OOH Media & Radio Mirchi. At present, I am the National Head of Strategy for Kinetic Worldwide and manage a portfolio of 277+ brands. 

Malvika: So how did you start interacting and developing an interest in Data?

Arijit: I have been in lead roles for proposing effective business strategies across leading brands. Good strategies are grounded in insights derived from data and not just gut feel.  Last year I received training on the basics of PowerBI.  I found it to be greater than just a business intelligence tool – and went ahead, post-training, to create 3 planning tools – used by my client servicing teams across the organisation.

Identifying the tool objective, getting the relevant data, cleaning and arranging the data into a usable form and finally coding its dashboards single-handedly was a very satisfying experience. It allowed me to work on large datasets which till then would run with great difficulty on MS Excel and make company laptops often crash due to excessive resource utililsation.

The first tool is a quick access dashboard providing bar, line, and Geo-spatial analysis for OOH investments by brands.

The second tool digitized out of home touch-point locations basis reach and affinity numbers from TGI.

The third tool enabled us to represent these touch-points across the top 45 cities/towns of India graphically. All these data points earlier spread across different data sources, Power BI allowed me to bring all these data-sets onto a unified platform and allow the client servicing teams to directly access the data and derive their own insights directly.

Developing these tools and eliminating redundant, repetitive processes for my team was my first pivotal interaction with Data Science.

Malvika: As a non-coder, how did you overcome the challenges you faced during coding?

Arijit:  INSAID offers weekend, online classes which allows me more time to invest. Simultaneously, I also explored more content on Python online and studied from multiple resources I could lay my hands on.

INSAID is a professional platform and I owe my learning and inquisitiveness to them. The well explained theories coupled with mentor motivation and encouragement is what you need. It’s all about developing a mindset of taking risk, and being willing to fail. So my three fold recipe is:

  1. Investing in-ordinate amount of time, 
  2. Trying without fearing failure & 
  3. Loads of Googling. 

Not only that, INSAID has a team of coders who are highly responsive and ready to help with any learning issues or specific input say code optimisation etc. as needed.

In-fact over the course of my learning journey – I have looked at python to automate common repetitive jobs that are done by my team daily in office.  An example was an audio file which required conversion to wav format; which I was able to do using just two lines of code in Python.  Not only that, very recently I have been able to automate batch processing of latitude and longitude variables for any location though a simple script.  This till now was done by manually looking up the location on googlemaps and copy pasting the lat and long coordinates into Excel.  

These were not part of my Data Science course at INSAID – but working on it has helped further my curiosity and confidence with the language.

Malvika: What is your advice to other aspirants to overcome challenges learning Data Science?

Arijit: As a learner I engage with the subject matter deeply. Unable to crack a concept or a theory is very frustrating. Trust me, learning Data Science is mostly very frustrating. But achievements give you pure joy and motivation to continue to the next challenge. 

Though the conversion of the above mentioned audio file was just 2 lines of code and less than 1 second of execution time – it required over three days of research.  Across these three days I identified multiple modules which seemed to be doing the job – but due to some reason or the other would not give the desired output.  Till finally – when I was nearly at my wit’s end  – I pushed myself to try once more.  And the joy of putting it together simply outweighed all the pain and anguish experienced during the last three days.

My instructor at INSAID said that the key to any learning is perseverance. Even though the highs are momentary and fleeting – its the effort needed to overcome the challenge – that makes it all worthwhile. A true analogy of my story with Data science.

Malvika: Thank You Arijit for your time. Good luck for your future!

Author

Content Writer @ INSAID. A machine learning buff who loves to read, write and explain everything AI!

3 Comments

  1. You are a huge inspiration for me. I was wondering how to start Python Starter kit. Now, I am confident I will be able to do it. Thanks for motivating

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