What if you need to elucidate any Data Science concept to any non-techie or a layman?

What if you need to elucidate any Data Science concept to any non-techie or a layman?

Explaining some concept to a layman (Image Source)

Itwas about a month ago when I paid a short visit to my hometown (Kolkata, India) and I was full of mixed feelings — excited because I was going to meet my family members after a long time, doleful as I was travelling alone, leaving my husband & my daughter here in USA and anxious because I was going to attend the visa interview(Student visa for pursuing my Master’s degree) at the US Consulate — the main purpose of my visit to my hometown. With all the mixed feelings going in my mind, I sometimes, became nervous too, with some questions like— “What if my visa gets rejected?”, “What if all my hard work of past 2 years in getting admission to the University goes in vain?” However, with all these questions buzzing around my mind, I went for the interview. Although I was expecting a lot of questions from the US personnel, it went pretty smooth as he was quite impressed with my profile. And, guess what, my visa got approved — “Yay!” My happiness knew no bounds. So, my dream of pursuing Master’s degree was soon going to be true. Everyone in my family was very happy and excited as I was.

And the days crossed by so soon and the calendar date was 14th July 2019 —when I would be flying back to USA from India. I would never forget that date in my life because something happened on that day which I was expecting on the visa interview day.

Are you guys wondering what strange thing happened that day? Well, here it goes:

Myflight was on 14th July, at 3:30 a.m. I entered the airport around 12:30 am and waved at my dad. He came along for see-off. With a heavy heart I went inside, waiting in the queue for my tickets. I got my tickets and then I was guided towards another queue — the Immigration Queue. I could see the big sign board hanging on the top displaying “Immigration (India)”. It was a big queue, the wait time was even longer. Anyways, I was waiting for my turn, unknown of the fact that I would be bombarded with a big pile of questions. Finally, it was my turn. So, the conversation went on like this:

Conversation (Image Source)

Immigration Officer (IO): “Hello Ma’am! How are you?

Me: “I’m good. Thank you. How are you?

IO: “I am fine too. Are you going to Chicago, USA?

Me: “Yes.”

IO: “Is this your first visit to USA? Oh my bad, I am so sorry. How can this be your first visit? You seem to be a frequent traveler and quite surprisingly you seem to possess so many visas — you have been on H4 visa for quite sometime, you had H1B previously and now you got your F1 visa also. Wow!

Me: “Yes, I have been staying with my husband as a dependent but now I have my F1 visa and would be traveling to USA with F1 status. And I have never actually traveled in my H1B.

IO: “So Ma’am, what is your purpose of your visit?

Me: “I am going to USA to pursue my Master’s degree from University of Pittsburgh.

IO: “Master’s in what?

Me: “Information Sciences

IO: “What will be your concentration area?

Me: “Big Data Analytics

IO: “What? What is that? Never heard of anything like this before. Could you please explain it to me in details?

Me: “If you have heard of Data Science, Big Data Analytics is a subset of that.”

IO: “No, these words are new to me. Explain them to me please.”

Now to be truthful, I never expected him to ask me to explain Data Scienceor Big Data, may be at the visa interview, but not here. So was a little dumbstruck for a moment, however then I thought he may create some problem if I don’t tell him something. So, I said aloud, ever the text-bookish: “Big Data Analytics is the complex process of examining large and varied data sets — to uncover information including hidden patterns, unknown correlations, market trends and customer preferences which help the organizations in making business decisions.

At that the IO looked at me silly and asked: “I didn’t understand anything. Can you explain me in some other way?

Me(in my mind): “OMG! What to do? He did not understand anything. How to make some guy understand the concepts of Data Science where he doesn’t have the faintest idea about it!

And then just like that I had this brilliant idea to explain about some aspects of Data Science.

Me aloud: “Have you ever tossed a ping-pong ball into a bucket in your childhood, as a part of the hurdle race?

Tossing a ping-pong ball into a bucket — towards perfection

IO: “Yes. Why not? But, why are you asking me this?

Me: “You might have realized that after the first attempt you have put too much force in it. The second attempt might make you realize that you were closer to the target but all that you needed was a little increase in the throw angle. So, what was happening there was basically after every throw you were learning something new and improvising on the end result.

Me (after a pause): “Does that make any sense?

IO: “Yes, it does.

Me: “Okay. Let’s take another example. Have you ever tried aiming at the dart? Was your every throw perfect? If not, what mistakes did you make?

Aiming at dart — a step towards making perfection (Image Source)

IO: “Well, frankly speaking. I was never good at aiming the darts. Initially, I tried to aim left or right of the real target but gradually my throw started getting better.

Me: “Exactly, after making few attempts you would realize that your elbow needs to be slightly pointed up directly at the dart-board. When you start the throw, your elbow leads to the process followed by the basic mechanics of your throw. The ultimate technique is — Aim directly at your target.

IO, again giving me the silly look: “Yes, I get it. But, what connects these examples to Data Science, or your course of study?

Me: “I am slowly coming to that point. The point I was trying to make is that we, rather, the human brain, is programmed to learn from our past experiences and eventually getting closer to perfection, if not 100% perfect always. And we can do something similar with machines too by applying the same technique. We can program a machine to learn from every attempts or experiences and then improve on the outcome.

IO: “Okay, I am not sure I am getting it hundred percent, but go ahead.

Me: “Okay, lets try some real application of Data Science — let’s say you have taken a day-off and planned for a long drive with your wife. Imagine yourself at the driver’s seat and your wife sitting beside you — you started the engine of the car, turned on the music, set the destination in your GPS and you are all set to go. After driving for one hour or so, all of a sudden, there is a forecast in the GPS that there is some road work going on and it has been causing traffic delays. Based on the information that the GPS has gathered from the satellites, it might be suggesting or predicting a detour for you or showing alternative routes to avoid any hustles and most of the time you would end up in an agreement with the GPS. Hence, you might understand how Data Science is making predictions in our day-to-day lives and trying to make our life trouble-free.

Me (with a pause): “I guess I was able to explain one of the application areas of Data Science, if not all.

IO: “Yes, of course. I understood what you meant and I am quite impressed with your explanation. I had no idea about Data Science and even was unaware of the fact that these kind of predictions might make a huge impact in our daily lives. Thanks a lot for educating me on this. Well, wish you good luck for your future endeavors and safe travels.”

Me (with a big smile): “Pleasure is all mine. Thank you!

And with a happy face I started walking towards the gate from where I would be boarding my flight. But that conversation made me realize that being from a tech background it is easier to explain some technical details to another techie, but your job gets more difficult when you have to explain the same to a non-techie in layman’s terms. When that person understands what you are really trying to portray, that day you can assume that you are “technically sound” and the concepts are clear in your head.



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