Driven by Data, an interdisciplinary field that uses Statistics, Mathematics and Programming to mine insight from the data and generate meaningful information for the management of the company to take strategic decisions that can help gain competitive edge in the market.
It deploys techniques and concepts drawn from Statistics, Mathematics and Computer Science such as Machine learning, Visualization, Classification and Cluster Analysis just to name a few.
It covers data cleaning, preparation and analysis of structured and unstructured data. Simply put, Data Science is an Umbrella term used for techniques for mining data and extracting meaningful insights from it.
Is Data Science much hyped career these days?
As Harvard Business Review quoted it to be “The Sexiest Job of the 21st Century”, the term became hyped and is now often used with Analytics in parallel.
McKinsey & Company projects that there would be a huge demand of 1.5 million fresh data scientists in coming years.
As per a report by Times of India, Data scientists earn more than Chartered Accountants and Engineers.
Glassdoor says that Data Scientist position ranks at No. 1 amongst the Best 25 Jobs List.
As per LinkedIn report, “Data Science & Data Mining skills are among the top job openings in most part of the world.”
These reports on the internet or search engines depict that the hype is real and yes, anyone who has sound knowledge of Statistics, Machine Learning and Programming can make it real big into the field of data science.
This fact can be very well supported by the following:
Thus, a study at Indeed.com/jobtrends suggest that data science hype is real and is the buzzword in the town.
Is there any real life example of Data Science?
Yeah, Data Science field has lots of application in the real life from Predicting who will buy, lie or die to Self-Driving Cars.
1. Amazon uses advanced Data Science/Machine learning Algorithm to provide recommendation systems for their customers thereby enriching the consumer experience on their portal.
2. Google Car/Self Driving Cars is also an example of Data Science Product that uses data and Artificial Intelligence to perform its operation in a seamless manner.
3. Google or any search engine at a random uses data science algorithm to showcase the best result for our searches.
4. Another interesting example can be Image Recognition that we see on Facebook. How facebook recognizes our friends & tags them is an impressive data science or Machine Learning Algorithm.
There exists several such examples that are changing our lives on a day to day basis and the world is getting better & better due to the intelligence provided by the data.
Today, data exists in almost all the spheres of life be it sports, insurance, banking, Govt. or any business at a random. This is one factor that makes the role of data scientists dynamic as they can be employed in almost all the sectors as long as data exists to provide them work related insights.
WOW!! Sounds like an Amazing Opportunity Ahead. How Can I make the Most of it?
To Become a Data Science Maverick or a Data Scientist so to speak, one must have the following to get going:
1. Genuine interest in numbers.
2. Should have Data Temperament which means can handle lots and lots of data without any trouble.
3. Must Have Analytical Bent of Mind.
4. Should be Willing to Learn
5. Practice, Practice & Practice
6. One must have sound knowledge of Statistics and Mathematics to make it Big in this field.
7. Amazing Communication and knowledge of Business/Industry.
These traits can make a person data maverick and a successful data scientist. Needless to say they should have profound interest in maths and statistics because data analysis and finding insights from the data can be performed with the help of these disciplines.
Tools that can make you a Data Science Superman
If you are willing to become a Data Scientist, You cannot ignore the knowledge of these tools.
The Big Question is to start with R or Python. People who come from statistics background prefer R when it comes to learning as most of the statistical analysis can be easily done on R apart from Excel.
However, the people who come from IT Background choose Python over R because of two major factors:
- The learning curve for R is much narrow in comparison to Python. Python is much easy to learn in comparison with R which means implementing data analysis, EDA and several other algorithms in python can be done conveniently as the learning can be replicated fast in comparison to R.
- Most of the Machine Learning Algorithms can be run on python easily and Python libraries such as numpy, Theano exist to solve the very same purpose.
Hence, it is essential to know R and python simultaneously because major startups prefer python as a core tool to perform major analysis. This can be very well represented by the following
Hence, a knowledge of R, Python and Machine Learning can make a person employable for lots of data science startups & the companies who are willing to hire Data Scientists.
There is one more concept which has evolved in past years & has become the talk of town – “Big Data.” Big Data refers to extremely large data-sets that are analysed to reveal patterns and trends in the data that can lead to better business decisions and strategic moves in business.
People who are skilled in Big Data along with above mentioned tools (R, Python and Machine Learning) can easily earn a handsome salary of 12 LPA as per Analytics survey 2017.
Note – This article gives an insight to beginners and helps them understand the buzzword – ‘Data Science’