Data scientists are the most demanded professionals today. That is the reason why there are so many offline / online training courses and certificates available in the market. But why is this field so bought after?

These days' manual jobs are replaced by machine learning, automation, and artificial intelligence. But to create these technological ways, one needs algorithms and models. But like all machines, they too are needed to be fed with prerequisites of data. Now data is present everywhere but in a raw form which needs to be cleaned and put in an understandable way, and this is where data science enters the scene.


Data science is extracting relevant and important information from raw data, which in turn can be used for taking strategic decisions in business regarding customer satisfaction and retention, demand and supply forecasting, development of a new product, understand market trend etc.

Several subjects come together here like mathematics, statistics, programming and most importantly business management. Also, it involves several processes like data collection and storage, data mining, data cleaning, data visualization, machine learning, and interpretation. Each of these is a job on its own and is usually done by few people together.


The number of companies offering analytics services is on a rise. Businesses from different sectors use data science in a different way, so their usage of analytics depends accordingly. Currently, big data industry shows a 33.5% growth rate and is estimated to be $ 2.71 billion dollars.

Banking and finance is the major player by generating 38% of the revenue, followed by digital advertising and E-commerce firms. The sectors that are growing in this business of analytics in the last few years are public healthcare, education, transportation, travel and hospitality, agriculture etc.


Almost every other sector is emerging on the analytics scene, but some of them have already started using it for their strategic promotion, like:

  • Agriculture: used for forecasting demand, predicting weather patterns, predicting the price of crops, forecasting the supply.
  • Manufacturing: used for knowing the demand and supply of raw materials, managing inventory, keeping a record of foremen and workers.
  • Transport: used for dismantling quick routes, flight plans, managing logistics of shipments, finding a cost-effective route, estimating delivery dates.
  • Healthcare: keeping and analyzing health reports of patients, estimating several rates like of child mortality, malnutrition, the need for hospital beds or facilities etc.
  • E-commerce: used for optimizing their websites, recommending systems, providing customer service, warehouse and inventory management, keeping track of customers and sellers.

Overall all these sectors use data science for increasing one's business value by taking timely decisions and solving analytical problems with efficiency.


To be a data scientist one should have mathematical, programming and business skills. Mathematical and technological skills are needed for cleaning, exploring and data model building tasks. Whereas business skills are needed for communicating the results to the management and for understanding the industrial requirements.

You can be mathematics graduate, a software student, a programmer or even a post-graduate in economics; you can pursue this profession with a good certification course and relevant training.