Day 3 – Case Study 1

Date – March 19, 2019
Time – 1:40 am

Case Study is a way of judging your logic and analytical capabilities. I can not be more vague with the definition 😛

Basically, solving or discussing a case study problem helps in knowing the way a person thinks. There is no right or wrong answer in solving a case study.
Let’s take a simple example:-
How will you increase the revenue of OLA or Uber or any cab service?

Candidate 1 :– Sir, increase the price and reduce the compensation given to the drivers.
Interviewer – Thank you so much Master, you saved me $100 Million Dollars, now duck off.

Candidate 2 – Sir, lets increase the number of cabs in the city, in the state, in the country, globally. Let’s have cabs floating on water and target Pacific Ocean.
Interviewer – Woooo..This is something where the whole team was stuck on. You are the next CEO of the company. Join in your next birth !!

Candidate 3 – Sir, We might be interested in knowing the peak and non-peak time of an area and then we might fluctuate the price(Basically surging ). We can also try a share service or we can enroll car owners to provide carpooling inter and intra-city.
Interviewer – Okay, let’s discuss the first point.

Look, Candidate 1 and 2 did not try to think out of the box and their proposed solution was also something which was way too obvious. I can say the same for Candidate 3 also, but there are few points on which he can continue the discussion and the interviewer can judge his/her thought process accordingly.

Let’s see how you tackle the below case:-

So, there is a company which stores your data in its cloud infrastructure, it has a free service for 6 months, then the customer has to pay some price to avail the service. The conversion rate is too less. Try to frame some possible reasons for the low conversion rate and what

Day 2 – What is Data? Why Data Science?

Date – 18th March 2019
Time – 2:42 pm

Before we start with Case Studies and Guesstimates, you need to know the difference between 4 terms which might look identical to you but are very different.

Data -> Information -> Knowledge -> Wisdom
This is called DIKW hierarchy, you can Google and learn a lot about this hierarchy, but since you are spending your precious time on this website, it’s my job to make you understand.

What is data?
Data is as simple as something raw. You will know something when you look at some data, but it will never give you a complete picture.
51 Centuries, 96 Half-Centuries, Sachin Tendulkar, India, etc. These are data.

What is information?
Information gives you a bit more detail about the above data. It is the collection of data. Using the above data points, I can give you information like

Sachin Tendulkar is an Indian Cricketer and has scored the highest number of Centuries in Internation cricket.

The above is some derivation of the data and eventually, we collected multiple data points.

What is Knowledge?
Knowledge is the awareness or conscious understanding of the information.
We have this information that Sachin is one of the best Internation Cricket, now the knowledge part will tell you that He is the backbone of Indian Cricket Team and He should be a part of the important cricket series if His form is not that bad because it will put a little more pressure on the opponent.

Now, What is wisdom?
Wisdom is the peak of this hierarchy. You look into data, frame information, derive knowledge and then put everything together.

Now, Dhoni is the captain of the team, the required run rate is high and we need 30 runs off the last 2 overs, the next batsman to come is Sachin(Yeah, the openers ducked it up). Now the wisdom of Dhoni will come into the picture and he will move up in the batting order and will come on the first down despite being a middle-order batsman.

The reason why we wanted to discuss it beforehand is to make sure that you have a good understanding of the term data and the terms which you think you understand !!

Why Data Science?
Don’t you want to crunch numbers to find out how many people will buy the latest iPhone from Amazon in the upcoming sale?
Do you get goosebumps by just thinking about creating an AI powered chatbot and make your friend go “Wooooo” while using it?
Don’t you get excited thinking about the impact your analysis will make, that too on the Higher Leadership level?

If the answer is NOOO, then Data Science is for you because we deal with really messy data, cleaning it with almost our bare hands and applying basic Linear Regression to fancy Neural Network to make the world free from errors(Ohkkk…I over-committed), but to be honest, it’s a really awesome and impactful job where you can actually be valuable for a company or your Client.

So, please don’t get motivated with a higher salary switch or adding something into your resume. Give some time to understand the capabilities of Data Science for the next few days.

First LEARN and then remove the L.

This was our 2nd class, you are doing all good and most probably you have read the first and second day of the course on the very first day(You engineersss !!!!)

Let’s start with the Case Study to understand “How to Understand a problem”.

Please come tomorrow, don’t rush today only 🙂
Same time, same place.


Day 1 – What is Data Science and How to make a career in it?

Ahh..I won’t lie, It’s quite simple to start a career in Data Science. You just have to be street smart 😛
There is no fix job or delivery when you work as a Data Scientist or Decision Scientist, you have to take up things as it comes to you.
One day you might be crunching numbers, the other day you might be creating data models to create a dashboard, the next day you might be creating a Recommendation Engine in a programming language you have never heard before, let alone having an experience in it !!

But, that’s the charm of the job, the challenge to deliver 🙂

Let’s start with Day 1, don’t rush. I can safely assume that if you are reading this post, you might be in one of the three buckets given below:-

1. I neeeed MONEY, I want to switch from an IT job, Testing profile
2. My Manager wants me to learn Machine Learning and Data Science. He said that I will get an onsite chance with this thing on the CV. Grow up, He is not sending you anywhere !!!!!!
3. I am a Data Scientist, but I don’t know Jack about Correlation, Auto correlation, I fail to understand things as simple as Standard Deviation. I want to Learn.

4. I have 2/3/4 years of experience and I want to switch to Amazon, Flipkart, Ola, Microsoft, etc etc. Cool 🙂

See, basically, I don’t give a duck why you landed on this page, but if you are here and If you follow this page like you follow your Boss, then by the end of 100 days, you will be better Data Scientist if not a better person 😛

Dictionary meaning of Data Scientist

Data Scientist (Noun) – Someone who does precision guesswork based on unreliable data provided by those of questionable knowledge

Also see – Wizard, Magician

Basically, Data is everywhere, whether you use an app or a website, every second a lot of data is being produced. The data is more like trash if you don’t know how to use it. But, if you can take up that structured or unstructured data and use some fancy scientific methods and algorithms to get insights from the same trash, then you will come to know the power of Data Science.

Uber is making Driverless car, you get recommendation on Amazon which is mostly relevant, you are shown relevant ads on facebook, all of these are small but important examples of how data is being used in today’s era.

On an overall level, I would say that a Data Scientist will be involved in at least these sort of projects in the first 4-6 years of his career:-
1. Extracting insights from unstructured and structured data
2. Building dashboards and maintaining reports
3. Writing SQL queries to solve ad-hoc request
4. Building products like a recommendation engine, predictive model, classification model, etc.

Data Science is the intersection of Mathematics Expertise, Technology, and Business Acumen. You will understand Data Science with time and by the end of the course, you will frame a different definition of Data Science which might or might not be correct, but you will be confident on it 😛

Below is a copied image, but there is no point making the same thing again. Below is a good image to differentiate between a Business Analyst and a Data Scientist. So, choose your role carefully:-

Once you are ready to walk along with me in this 100 Days Challenge, do say with me “Tum mujhe Data do, Main Tumhe analysis dunga

How to make a career in Data Science?
Let’s divide the complete course or your data science career in few parts:-
1. Query Language – Your bread and butter, SQL
2. Visualization Tool – The thing which will please your Client or Boss, Power BI, Tableau, etc.
3. Programming Language – I would prefer Python over R, any time and every time
4. Statistics – Please don’t ignore this part, you can never get enough success without acing Maths and Statistics.

Once you get some knowledge about everything, you will start connecting the dots to see that a complete Data Scientist is an amalgamation of all the four given above.

Enough for the first day, Chillax guys. Make sure, you come tomorrow for the class. Same time, same place 🙂