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As we enter , we say goodbye to a long decade of technological advancement and information augmenting the business landscape globally. That means a new beginning is on its way. A beginning that is poised to bring in a gamut of changes, ideas, innovation, information, and obviously some new challenges.

Businesses that possess information are looking to make intelligent use of this otherwise junkish data. That naturally gives way to data analysis and data science technologies. Subsequently, it is critical to comprehend what is data science and how it is valuable for businesses of the information age.

A great example is social media networks, and the way Facebook and similar legacy platforms have leveraged the power of data such as user demographics and interests to bring endless solutions for business owners and individuals.

The data science domain employs mathematics, statistics, computer science, and information science to analyse and understand data.

The final results and information are then converted into ideas, solutions, and offerings by the business decision makers. It is really easy to understand the available structured data like that of Google Analytics that helps us ascertain the type of users visiting our platform.

There is a lot of unstructured data available with organisations that can help their offerings to be much more personalised. In comes data science! It is used to analyse and draw meaningful insights out of semi-structured and unstructured data, various advanced analytics tools, and frameworks like Power BI, Apache Hadoop, Spark, Tableau, and programming languages like Python, which help carry the load. Talking about the use cases, there is no stop to the implementation of data and tools to make a difference in business or changing lives.

Here are the cornerstone use cases of data science:. There are a number of case studies such as Flipkart vs. Walmart by Data Flair backing the importance of data science in terms of minimising losses Data science has facilitated rapid growth in industries and has minimised their losses.

With the ever-evolving, competitive business landscape, it has become critical to understand the users and their requirements precisely. This helps to assess the gaps and come up with ideas and offering. Artificial intelligence and machine learning are the new cool as demonstrated in movies such as Iron Man. Taking a more real-life case, having a self-driving car today is entirely the outcome of processing data, utilising machine learning algorithms, and implementation of instructions by the machine.

Weather forecast is a great example of predictive analysis. It is required by space research organisations, media portals, and the aviation industry. The data pulled from radars and satellites is analysed and used to provide predictions related to weather changes and natural calamities.

Industries such as telecommunications and social media, which are attracting millions of users and subscribers daily really need to moderate the activities of the users. Frauds such as illegal access, theft, impersonation, Jon Boat Manufacturers In India Key cloning, and any other such activities can be monitored and prevented with data science. Doing business in the digital era needs accumulating data and analysis to bypass competition and identify user interests.

Businesses in India as well as globally are deploying the data tools not only to ease up the product development process but also to bring the unique offerings that society lacks today. India is undeniably one of the cornerstones of the IT industry today. Enterprises today leverage the power of data to hire, train, and improvise functions within organisations. IBM has predicted that the demand for data scientists will soar 28 percent by It is the very need of the hour for organisations to hire employees armed with data science to create relevancy with the market requirements and sustain in the competitive business environment of the present and the future.

A report published by Express Computer back in July outlines how OYO utilised data science to come up with a distinctive offering making a mark in the hospitality sector of India. According to The Hindu, at the beginning of , there were close to 97, data analytics jobs vacant in India, of which 45 percent lie in data analytics companies. All this makes data science a hot career choice. As a data analyst working for an organisation, you are responsible for analysing large amounts of complex data, identify patterns, and derive conclusions carried forward to make prudent business decisions.

As a BI developer, you contribute towards organisational growth by developing strategies. You need to deploy various BI tools and build custom models to facilitate understandability for the leaders of an organisation. Data architects ensure maximum performance built by data scientists and developers by testing and demonstrating the results. Applications architects track the behaviour of applications used within a business and how they interact with each other and with the end users.

Infrastructure architects ensure the optimal performance of systems to contribute towards the development of new technologies and system requirements. A great example of this role is a very trending one - cloud infrastructure architect.

An enterprise architect works closely with the stakeholders of a company including the directors, VPs, founders, and other top-level managers to build enterprise level IT assets. One also needs to possess managerial skills to be eligible for this role. Machine learning scientists understand the binary language behind the applications and models.

They perform batch processing of accumulated data to make it readable for data scientists. As a machine learning scientist, you are also responsible for researching new data approaches and algorithms, create data funnels, and deliver solutions.

Being technical and analytical to the core, the data science domain requires expertise in various disciplines including, mathematics, statistics, IT, and computer science. Some common educational qualifications required to become a data scientist would be:. Data scientists in India earn an average of Rs , in a year. While the job roles and opportunities associated with the data science domain are appealing, these involve a steep learning curve, experience and a technical background - making data science a tough domain to crack.

The steep learning curve associated with data science is evidently the reason behind the ever-increasing demand and shortage of supply of data scientists in India. And therein lies its potential. Disclaimer: The views and opinions expressed in this article are those of the author and do not necessarily reflect the views of YourStory. By Pradeep Chopra 6th Jan Share on. How Navigus uses Data Science to help students and professionals maximise their probability of success.

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