Why are Data Science skills the best for youth ?

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As organisations see the importance of data in strategic decision-making and process automation, it has become more important to enterprises across all industries. The areas of data science and analytics have witnessed significant expansion in recent years.

To improve their business outcomes, an increasing number of companies rely on data. It's not only about technology when it comes to data science. Every industry nowadays collects user data that must be analysed in order to make the best decisions, from pharmaceuticals to retail, manufacturing to aviation. Data science is a broad phrase that does not refer to a specific skill set. It's a professional path similar to engineering or management. What's essential for young people is that when they first start, they want to know everything. But the most essential thing is to get your career started, since you will learn and unlearn a lot as you grow. New tools will emerge, and technology will continue to evolve, therefore you must continue to upskill. However, the necessity for educated specialists to work with vast volumes of data and make critical business decisions based on that facts will not alter.

Data science remains one of the top occupations according to LinkedIn and Glassdoor. Although most employees in the field have less than two years of experience, the power it has on the business is enormous. In the United States, a data scientist's typical pay ranges from $117 to 120K, which is significantly greater than that of a seasoned software engineer. So, from a young person's viewpoint, these are two significant measures in terms of data science as a rewarding job.

What is Data Science so important in today's world?

The four aspects include the convergence of enormous and exponential increases in data, as well as the 3Cs - cost, computing power, and capability.

Data will become the new oil, and everything will revolve around it. Data science is nothing more than the interpretation of data for the purpose of gaining insights. Data will be the driving force behind all of humanity's future endeavours. The age of data is here, and whether we like it or not, we will all be drawn into data sciences and data information practises, consciously or unwittingly. The total adoption of Analytics & Data Science at large Indian enterprises is about 74.5 percent, which is a good percentage given that the majority of these large Indian corporations are in legacy industries like electricity, steel, and energy. The demand-supply gap, on the other hand, is a source of concern. Job openings increased by more than 64% between 2018 and 2021, while the supply gap worsened by nearly 125 percent.

In India, there are a hundred thousand data science jobs, with at least 60-70 percent of them being entry-level positions. However, the company's recruiting procedure is stringent, and you must pass it. Job vacancies do not guarantee that you will obtain the same job if you walk in; you must have specific skill sets and be able to demonstrate those skill sets. Understand the field; becoming a data scientist is a long process. It takes time and practise to master. You'll start as a data analyst, business analyst, or data engineer; learn what that position entails, and if it intrigues you, then master those skills. This will prepare you for the market, and you will subsequently acquire exposure.

A job in data science does not need becoming a computer science engineer. Every year, we receive and place hundreds of students from non-CS backgrounds. These students may be mechanical engineers or not at all. They might have a bachelor's degree in business or a master's degree in computer science. You don't have to be a mathematician or a statistician, but you can't be a math hater either, because data science is impossible without math and fundamental statistics.