Upskilling: A Powerful Tool for Future Data Science Jobs

Ever since the disruptive technologies like AI and data science have made their way into the mainstream IT industry, there has been a constant emphasis on unlearning – the old skills and learning the new ones. Implying you must constantly update your skills to stay relevant in the industry.

In short ‘Upskilling is the way to stay in demand.’

The question is – was the need for constant upskilling new or was it always there but never got its due importance?

Read this –

Julie Friedman Steele, Board Chair of the World Future Society says, with the rapid digitization it is imperative for the society to adapt and constantly keep our learning curve growing.

So constant learning is the key to stay in the game. Constant learning implies both reskilling and upskilling. However, upskilling is the concept that we will be talking here.

Upskilling – What Is It?

Upskilling is defined as learning additional skills or to give a boost to the existing ones in order to move further in one’s career. Going by the definition is not difficult to guess, why upskilling is the new buzzword in the field of data science.

Picture this –

According to the Future of Jobs Report by World Economic Forum (WEF) –

-The Fourth Industry Revolution will create about 133 million new jobs by 2022.-At the same time about 75 million jobs will become obsolete in the large organizations.

Inferring – Professionals who lack the requisite skills like data analytics will be replaced by those who have been constantly upskilling themselves.

Industry 4.0 Revolution and Need for Upskilling

Numerous industry experts including Accenture, the World Economic Forum, and a other global organizations reveal that Industry 4.0 is here and there is no time for preparation. The Fourth Industry Revolution demands acceleration including continuous technological changes like automation, AI, and digitization, increased complexity in businesses and business models that are based on new disruptive technologies.

Result: A huge transformation in how the workforce is structured along with nature of jobs in the future including the types of jobs that will be available in the coming years.

Implying: Professionals will need to upskill themselves in order to stay relevant, as the older skills will become redundant.

The report concluded with the thought that everyone – the entire workforce will be impacted irrespective they are working in a low skilled or in an expertise role.

Importance of Data Science and Why You Need to Upskill

Before we delve into the importance of Data Science for the current businesses. Let’s understand what data science is and why has it become an essential part of the current business practices.

In simple words Data Science comprises study of raw data that organizations receive non-stop from various channels with the help of advanced techniques and tools to convert that unintelligible data into meaningful business insights. Result: Well-informed decisions that gives businesses an edge over the competitors.

Data Science professionals use various techniques like machine learning, mathematical skills, along with programing languages that are AI-based. The main aim of data science is to analyze and structure it in a way that it can be interpreted easily to draw conclusions and have an edge over the competitors.

Here are some of the reasons why Data Science has gained importance in the current workplace

• Data Science helps in client recognition in a more streamlined manner. Data Science algorithms allows businesses to connect with the right clients thus paving way for meaningful and fruitful future relations.
• Data Science is all about storytelling through meaningful and insightful data. It creates better ideas thus ensuring better connections between the businesses and customers.
• Even non-technological organizations can apply data science to predict better results for their businesses and take advantage of data science to make informed decisions, figure out the challenges, find proper solutions to the problems.
• In the current workspace, data is considered important and what’s more one can apply data science algorithms in any field to get insights that are important for business growth and goals achievement.
• Data Science will also help in building deeper connections with the clients along with deeper understanding of how the products are used by the clients.

Despite all these advantages, and the growing demand for data science professionals in the market, there has been a skill shortage in data science professionals. While there has been an upward surge in data science jobs, there has always been a huge gap between demand and supply of skilled data science professionals.

Reason: Data Science career requires constant learning and upskilling.

With the technology evolving at a faster pace than ever, it is imperative for data science professionals to be on their toes and be one step ahead of the technology by constant data science upskilling. One of the best ways to upskill yourself is to opt for Data Science Certification that will authenticate your upskilling.

Not only that since certifications come with an expiry date you will constantly try to upskill yourself to stay relevant for the same data science certification or opt for a higher one. Either ways data science upskilling is the name of the game.

Data Science is the Future of Jobs

Remember that data is at the helm of every business today, so data science is here to stay, In fact, it is the future of jobs. So if you wish to stay in the field, you need to upskill yourself for a successful data science career.

There is a tremendous growth opportunity in the field of data science, as every industry in the present day relies heavily on data science. For those seeking a data science career this is the right time to step in; analyze your existing skills, and upskill yourself as per the industry demands and see your data science career soaring high.