FUTURISTIC SKILLS: DATA SCIENCE

“Information is the oil of the 21st century, and analytics is the combustion engine.”

– Peter Sondergaard of Gartner Research.

The world we will live in tomorrow will be significantly different from what we live in today. I would not be surprised if the house maid gets replaced by a robot or your newspaper gets replaced with a tablet based online news or the chauffeur gets replaced by a self-drive car or your assistant would be your cell phone / laptop. The list of jobs which will eventually get replaced by Technology can go on. We have already seen the move from call centre operator to a IVR format. Visits to Bank branches have reduced.

This change is happening relentlessly. Even right now while you are reading this article, some one somewhere in this world is getting replaced by technical advancements.

Today more than any time earlier the distinctions between the different domains are vanishing. Mechanics is merging with Electronics to form Mechatronics. Doctors are coding the software’s that will give medical advice / Lawyer’s will code software’s to give legal advice.

I do not mean to scare you with this thought. With the advent of new Technology there will also be advent of new Skill Sets that will be in demand. To name a few:

  1. Data Science.
  2. Artificial Intelligence.
  3. Mechatronics.
  4. Supply Chain Management.

The list here as well is long, though it is debatable whether the human intervention / need will increase of decrease? But still there will be some strong skill sets which will increase in demand.

In this series of Futuristic Skills, I will take you through a few skills, I suppose will form the back bone of the future job markets. To start we will discuss first about DATA SCIENCE. So let’s dive-in:

Wikipedia defines Data Science as: An inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data.

So just to simplify the same, we are all aware that we are drowning in data today. We have far more data available compared to time for analyzing, processing or scrutinizing the same. Data Science is a field which uses algorithms (computer programs) along with some statistical models to give you what you are looking for in a data.

Kind of Finding a needle in haystack.

Imagine

How does a Mall around the corner decide on which products to keep for sale? / Which products to be placed at which location?

How does Tesla decide on how to market their cars?

How does Amazon / Flipkart decide on where to keep stocks of which products?

How does a bank decide the location of their ATM’s

All of the above are examples of Data Analysis. They gather data of there customers / orders / Target audiences, then they analyse the same with cost of marketing / stock / location, then they arrive at a winning proposition of Low Cost to High Conversion and implement the idea.

This basically is what Data Science is all about.

Let’s start to understand a bit more in details:

DATA: Data is a Raw Information. Where does this data come from? It is collected all around us, every moment. Example:

  1. When apply for a job, you give your preference for a City, domain, years of experience, educational qualification, etc.
  2. When you buy a product / cell phone card, you give out your address, birth date, alternate no, etc.
  3. On Social media platforms, we unknowingly disclose our Birthdates / Anniversaries / Kids Birthdates / names / Age / Travel locations / Political preferences, etc.
  4. Now a days there are umpteen online Quizzes’ – which celebrity do you look like? / What house will you live in? / How will then older you look like?
  5. There is umpteen data collection avenues.

All of this is Unstructured Data – In its Raw form no one can make any major use of it. But when you structure the same data, it can be of amazing use. We will see this in details in our case study further.

SCIENCE: So utilizing this unstructured data and using some scientific and logical steps – we can form a string of statements, which can be used to define Business Strategies.

So what are the steps in Data Science:

  1. Configure the correct question.
  2. Compile the Raw Data post processing & cleaning.
  3. Primary Data investigation.
  4. Scan the Data with one or more Models and Algorithms.
  5. Derive results using the Data Science techniques of Machine Learning, Artificial Intelligence & Statistical Models.
  6. Discuss and improve on results with stake holders feedback.

CASE STUDY: Let’s take a very simple case study for the Data Science:

  1. Question to be answered: Target Customer for Old Age Medical Services.
  2. Compile Raw Data: Hire 10 People who collect the following data by visiting all household in a certain defined area.
    • People in Household.
    • Their age
    • Any Ailments – e.g Diabetes / High BP / Low BP / etc.
  3. Primary Data Investigation: You sort all those houses that have Older people living.
  4. Scan the Data with Models: Then you apply Specific Age / Disease criteria to find your Target Homes.
  5. AI: You feed these Nos to your Auto SMS / whats app messages service and keep pushing notifications / Advertises of your Services.
  6. Compiling the results of your 1 Month / 3 Months response you again fine tune the above process.

I hope that I was able to bring clarity to you on the topic of Data Science. I will take on a new topic for the next article on the series of Futuristic Skills.

Do let me know in comments below in case you need any more information / have some thing more to add to this topic.

If you want to know more on the subject and courses that you can do, please check the following links:

EDUCATIONAL REFERENCES: Please find the links for more articles and courses.

Upgrad: PG Diploma Course from IIT B  

Simplilearn: PG Diploma Course with IBM  

Edureka: Article & Courses

Udacity: Courses on Data Science

Leave a comment