many uses of data science
"Ladies and Gentlemen, This is the final gold coin from the lucky draw to be handed tonight, are we all excited and ready to know who is the lucky fifth?"- Said the compeer of our family day event yesterday. My colleague's 6-year-old daughter picked out a chit from the bowl placed on the stage and handed over to the compere. At first, the lady in dazzling blue outfit could not pronounce the name written on the chit, courtesy the illegible handwriting. The chit had to be passed on to the human resource manager, with the thought that she had decryption key for the dancing letters written on the chit. Sitting in the 10th row in front of the stage, I mumbled- How good it would be if my name could be announced, and my luck would favor me just once. HR announced my name as the final winner of the evening. Surprised and elated as I walked towards the stage to receive the coin, I kept thinking - is there a scientific explanation for luck, or is it a conspiracy of our stars?
My family had immense belief in Astrology- a pseudoscience, which claimed that the planetary positions at the time of our birth have a significant influence on our intellect, academics, health, and profession. When we found that my sister had a hole in her heart and the astrologers had predicted that she would not undergo surgery in her lifetime, we interpreted the statement that her heart would get healed up automatically by some miracle. Little did we know that the prediction indicated that she would pass away at a young age of 34 without getting a chance to be operated.
Fast-forwarding to the present, we still have faith in the power of the celestial bodies. In the culture where I come from, the majority of the marriages are not out of love but arranged by the family after matching the horoscopes- even though in today's millennial, we can find a partner via matrimonial or dating websites. Nevertheless, we see a rise in failed marriages and divorce cases from a 100-200 in the 1980s to about 9000 cases per annum today. Can data science be used to decipher the code of healthy relationships; relationships that sustain the test of time? Can data science inspire us to become better managers, better children, better doctors, and better life partners? Can data science combine astronomy and mathematical models to unravel the truth behind the most widely believed pseudoscience Astrology?
After spending 13 years in the software industry and growing well professionally, I reflected upon what I missed on the personal front. I had supportive parents and siblings, a warm group of friends whom I can connect with frequently, and my laptop and mobile devices for emotional support. Yet when I looked around, all I could see people walking on the roads with their heads bowed gazing into their iPhones with less inclination to spend time with living beings-our web presence was overpowering our presence with our loved ones. One of my friends poured out her emotions of being ill-treated by her husband while another had a narrow escape from a house where she was locked up by the man she trusted the most. While I came across numerous such stories, I realized that while Data science can be used to find the patterns of television viewing, consumer preferences, fraud detection or build financial risk management software, the need of the hour was to use Data Science to de-mystify the algorithm of successful relationships- not the relationship between Data Science, Big Data and Machine Learning, albeit the complex human relationships.
In order to break the ice with Data Science, I took up a beginner's course in Data Science and Python from Coursera. Not only did I learn Python, but I also re-found my love for data and statistics while exploring the Quantlib library of Python. Completing the course within four weeks gave me the confidence to take up the role of Python developer and even develop frameworks for integrating python libraries and Jupyter notebook with my current organization's products. I understood the potential and impact of mathematical models, predictive analysis to create innovative solutions. The brief glimpse into Monte-Carlo simulations, Heston, and Hull- White calibration algorithms helped me understand Python and R syntactically, but numerous pieces of the puzzle are still missing.
