Why do Companies Need to Invest in Data Science in 2022?
In today’s world, nothing is constant. From the flow of information to the tools used to improve or even replace physical labour as a whole, everything is in a constant state of evolution. Analog is rapidly becoming a thing of the past and the realm of science fiction is gradually changing into an experimental science. Elements like Augmented Reality (AR) and remote controlling of drones already prove that technology is the window to the future and multinational corporations like Google, Microsoft, and Apple have shown us how possible it is to monetize on the said change.
One of the pillars of technology that supports the dream of a fully digitized future with streamlined information is Data Science. The fact that the field is related to big data, data mining, and machine learning should speak for itself. On the same wavelength as but fundamentally different from computer science and information science, Data Science deals in unifying informatics, statistics, and data analysis at their grassroots level. As it is a study of data itself, the field draws from theories not only in computer science and information science but also in domain knowledge, mathematics, and statistics.
To further understand Data Science, one must know why more and more individuals are turning to it by the day. Some reasons for its rising popularity are as follows.
1) Demand in career: Given the fact that is currently the fastest-growing career on LinkedIn and is estimated to spawn around 11.5 million jobs by the end of 2026, a potential job hunter will see a massive opportunity in Data Science.
2) Too many empty positions: Since it is a relatively new field of expertise, not many people have acquired the skills to be considered full-fledged Data Scientists. Those who have are very few in context to the total number of available positions. The lack of saturation makes Data Science a prospective area for career seekers to aim for.
3) A satisfactory income: Money is often a deterrent for potential employees eyeing a department. But income is nothing to worry about when it comes to Data Science because according to a study by Glassdoor, established Data Scientists earn around $116,100 per year.
4) No stagnancy: If you feel like you do not belong to one small cubicle throughout your career, Data Science prides itself on its versatility. From consultancy services to banking to e-commerce industries to even healthcare, Data Science is applied in numerous fields.
5) Say goodbye to repetition: One of the biggest overhauls brought about by Data Science is automating redundant tasks. Companies are gradually starting to train machines using recorded data to replace humans in performing arduous repetitive tasks in daily life.
6) No one says no to prestige: If you are worried about a lack of recognition for your efforts, a Data Scientist gets more than they ask for. Since their expertise in the field plays a big role in providing better results to clients, they are highly respected in companies.
As society keeps overhauling parts of the social framework into their digital alternatives, both big and small organizations lean on data management for efficiency. It is there that Data Science plays a big role. Since it is an arbitrary subject, many takers initially decided not to put their trust in an untested field. Over the years, however, Data Science has proven to be a handy tool to have under one’s arm. Here are some of the recent contributions of Data Science that throw light on why budding or established companies should invest in Data Science in 2022.
1. Contributed to making better business decisions
Since Data Science deals with the management of data, it is a given that it boosts the decision-making process. The act is thanks to the ability to view data in real-time, providing better flexibility to business managers. That, in turn, enhances business growth.
2. Facilitated the gaining of customer insights
Have you ever wondered why Amazon suggests a specific brand of watch seconds after you looked it up on the internet? Or why there are ad pop-ups on social media about a specific vehicle right after you clicked on a post about it? Data Science segregates data by demographics, habits, characteristics, and preferences to generate appropriate customer insights and predict customer behaviour.
3. Helped in the improvement of data relevancy
Following the same formula as predicting customer behaviour, Data Science analyzes recorded data, assesses the current market, and recommends the place and time where the launch of a product would have the best effect.
4. Provided the resources to appropriately increase data security
With the increase in digitization on a global scale, insecurities also grew regarding data theft. Thus, Data Science incorporated the use of complex Machine Learning algorithms along with multi-layered encryption processes to protect sensitive business information.
5. Enabled the hiring of top talents with untapped potential
The manual sorting of a physical database not only takes time but also retains the risk of overlooking a potentially important file. On the other hand, Data Science uses analytical processes based on data points from corporate databases, social media, and job ads, making it easier to recruit and select the employees that fit the requirements of the organization best.
Considering the current state of information flow and management, big data is rapidly being recognized as a necessary tool for the same. It has not only changed the fundamental nature of business models but also facilitated the creation of new ones. If you can look beyond the problem of data privacy, Data Scientists are irreplaceable assets owing to their skills in creating software and algorithms that determine optimal operations by breaking down big data into usable information.
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