Data Science has been hailed because of the “sexiest job of 21st Century” by Harvard Business Review. But what makes Data Science so important? Why are Data Scientists a number of highly paid professionals? And most importantly, why learn Data Science? In this article, we’ll rehearse a number of the foremost reasons on why Data Science has become the most wanted job within the market. We will understand the wants of companies and why they have Data Scientists to spice up their performance.
Before moving on we recommend you to first check what exactly Data Science is.
Understanding the Scenario of Data Science
Glassdoor has ranked Data Science as its topmost profession. What has made Data Science so relevant today? the solution lies within the massive exponential increase of knowledge. Data is the fuel that drives industries. Big Data has revolutionized companies and has given them a foothold in competition. These companies need specialized people that are proficient at handling, managing, analyzing and understanding trends in data.
For example – a corporation that desires to maximize its sales revenue would hire a knowledge Scientist to research its performance and supply decisions to maximize it.
This has created a pressing need for hiring more Data Scientists. So, why must you learn Data Science?
The answer lies within the incontrovertible fact that there’s an enormous discrepancy within the demand and provide of knowledge Scientists. There are more vacant positions than the number of knowledge Scientists during this world. Since there’s an enormous demand, companies pay astronomical figures for these positions. Therefore, you ought to learn Data Science so as to tap this chance and enrich your career.
Why Learn Data Science?
Here are the reasons that will surely convince you to make a career in Data Science:
1. A fuel of 21st Century
In the last century, oil was considered because of the ‘black gold’. But, with the economic revolution and therefore the emergence of the automotive industry, oil became the most driving source of human civilization. However, with time, its value dwindled thanks to the gradual exhaustion and resorting to alternative renewable sources of energy.
In the 21st century, the new drive behind industries is Data. As a matter of fact, even automobile industries are using data to impart autonomy and improve the security of their vehicles. the thought is to make powerful machines that think within the sort of data.
Data Science is additionally the electricity that powers the industries of today. Industries need data to enhance their performance, make their business grow and supply better products to their customers.
In the scenario of the knowledge science section, we took an example of a billboard industry that desires to maximize its sales. so as to try to so, it requires a radical analysis of knowledge behind sales, understanding of the purchasing patterns of the clients and using their suggestions to enhance the merchandise. To perform these tasks, a knowledge Scientist is required.
Similarly, take an example of a Business Intelligence company that is required to research its potential customer base. It requires a knowledge Scientist to utilize the info they breathe on the web to trace their daily trends and analyze their behavioral patterns.
1.1 How Does a Data Scientist Make Sense of Data?
A Data Scientist will use his tools to sculpt through all this data and chisel out meaningful observations that will help companies to make profound decisions. Similarly, a health-care company specializing in building conversational platforms for patients of mental health will need data to analyze the trends and patterns. Automobile industries need data to develop self-driving cars.
Data is being generated since the dawn of human civilization. However, only recently we have been able to tap its true potential and draw insights from it. Only in the past decade, we have started to depict data as a fuel for industries. The main contributor to this latest revolution is the rise in computational power
1.2 High-Performance Computing – An Answer to Complex Data
With the advent of high-performance computing platforms like
We have been able to process such a voluminous amount of data. We are able to analyze and draw insights from this data owing to these advanced computational systems. However, despite all these advancements, data remains a vast ocean that is growing every second. While the huge abundance of data can prove useful for the industries, the problem lies in the ability to use this data.
As mentioned above, data is fuel but it is a raw fuel that needs to be converted into useful fuel for the industries. In order to make this raw fuel useful, industries require Data Scientists. Therefore, knowledge of data science is a must if you wish to use this data to help companies make powerful decisions.
2. Problem of Demand & Supply
As discussed above, there’s an enormous abundance of knowledge. However, there aren’t enough resources to convert this data into useful products. That is, there aren’t enough people that possess the specified skills to assist companies to utilize the potential that data holds. thanks to this reason, there’s a scarcity within the supply of knowledge Scientists.
Much of this is often contributed by the infancy of knowledge Science as a field. there’s a scarcity of ‘data-literacy’ within the market. so as to fill this vacuum in supply, you would like to find out Data Science and its underlying fields.
Data Science isn’t a standalone field. it’s comprised of several sub-fields. These subfields are Statistics, Mathematics, computing and Core Knowledge. Data Science offers a steep learning curve and is difficult to master.
However, with the proper resources and direction, one can undertake the journey of mastering Data Science. an excellent data science product is sort of a meal composed of knowledge as its raw ingredient, tools like programming languages wont to cook the meal and therefore the foundational knowledge of statistics & math as its recipe.
2.1 How to Cover the Skill-Gap?
To assuage the high demand, people should direct their attention towards learning the required skills which will help them to require up Data Science as a prospective career. While there are many resources and books on the web , it’s impossible to digest everything all at once. Therefore, people must curate a path and do away with all the required clutter to possess practical insights about Data Science.
To create a refined data product, we’d like refined and polished skills. This comes with a mixture of data and knowledge. Since Data Science may be a recent field and thus experience can take a back seat. However, it’s built upon existing knowledge of maths and statistics that one must realize.
Data Science is about the implementation of this data through several tools and programming languages. Therefore, one must also possess the talents of a scientist. Data Science in simple words is often termed as applied statistics without computing. The proficiency of those tools may be a must since you would like to precise your knowledge in the right manner. It is, therefore, an utmost necessity to find out all the subfields of knowledge Science so as to understand the trends hiding within the data.
There is a pressing got to fill the skill gap so as to churn out Data Scientists required by industries for his or her versatile applications. Therefore, we will best conclude that learning Data Science isn’t almost one topic but a set of varied topics starting from Statistics to computing. One can learn data science within the right manner by walking within the right direction and curating topics that ascertain the sensible implementation of it.
3. A Lucrative Career
According to Glassdoor, the typical salary for a knowledge Scientist is $117,345/yr. this is often above the national average of $44,564. Therefore, a knowledge Scientist makes 163% quite the national average salary. This makes Data Science a highly lucrative career choice. it’s mainly thanks to the dearth in Data Scientists leading to an enormous income bubble.
Since Data Science requires an individual to be proficient and knowledgeable in several fields like Statistics, Mathematics, and computing, the training curve is sort of steep. Therefore, the worth of a knowledge Scientist is extremely high within the market.
A Data Scientist enjoys the position of prestige within the company. the corporate relies on his expertise to form data-driven decisions and enable them to navigate within the right direction. Furthermore, the role of a knowledge Scientist depends on the specialization of his employer company. for instance – a billboard industry would require a knowledge scientist to research their sales.
A health-care company would require data scientists to assist them to analyze genomic sequences. The salary of a knowledge Scientist depends on his role and sort of labor he has got to perform. It also depends on the dimensions of the corporate which is predicated on the quantity of knowledge they utilize. Still, the pay scale of knowledge Scientists is much above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the quantity of labor that they need to put in. Data Science needs diligence and requires an individual to be thorough with his/her skills.
Due to several lucrative perks, Data Science is a beautiful field. This, combined with the number of vacancies in Data Science makes it an untouched gold mine. Therefore, you ought to learn Data Science so as to enjoy a fruitful career
4. Data Science can make the World a Better Place
Big Data & Data Science is beyond being a tool of Business Intelligence. Various philanthropic and social organizations are using data to make products for social good. Also, various health-care organizations are using data for helping doctors to possess better insights about their patient’s health.
In this section, we’ll undergo various examples where companies are using data for social good. this may assist you to develop inspiration to find out Data Science as a tool for enriching the lives of individuals.
4.1 Data Science for Analyzing Refugee Crisis
The global refugee crisis has become a problem that has resulted in deaths and the displacement of many people. In order to manage and regulate the information of refugees, the United Nations and World Bank have established a center for this purpose. Using data based on gender, age, income, skills, and health, will analyze and take decisions to help and improve the lives of displaced people. It will use data to help displaced refugees and asylum seekers through real-time access to refugees. Therefore, Data Science is playing an important role in assisting governments and policymakers to make better decisions.
4.2 Data Science in Healthcare
Another major usage of knowledge is within the field of drugs and health-care. Various health-care industries use historical records of knowledge to predict diseases and help in early diagnosis. With the arrival of deep learning algorithms in data science, it’s possible to detect tumors and other defects at an early stage of diagnosis.
Data Science is additionally helping genomic industries to research the effect of the medicine on genetic issues, analyzing genetic sequences and developing new drugs to combat diseases. In these ways, Data Science helps people in various socioeconomic and health sectors.
Therefore, we realize the necessity for data and data scientists to assist the planet to become a far better place. we’d like to find out Data Science so as to make better solutions for real-world problems that folks face today. There are problems all around you. you would like to acknowledge problems and develop solutions using the prevailing data. this may inspire you to find out data science as you’ll have a goal towards solving the matter.
5. Data Science is the Career of Tomorrow
Data Science is the career of the longer term. Industries are getting data-driven and new innovations are being made a day. the sector of technology has become dynamic and with more and more people interacting with the web , more data is being generated. Industries require data-scientists to help them in making smarter decisions and creating better products. Data perceives because of the electricity of recent gadgets and applications. It makes products smart and empowers them with autonomy.
In today’s world, it’s become a necessity to possess data-literacy. We must find out how crude data can transform into meaningful products. We must learn the techniques and understand the wants to research and draw insights from the info.
Data holds an untapped potential that has got to be realized so as to develop useful products. With the arrival of machine learning technologies, it’s now possible to predict and intelligently classify information. Big Data and Data Science hold the key to the longer term.
Before its too late, Start Learning Big Data
Together, they form the larger picture of AI that’s giving us products of the longer term like Self Driving Cars, Autonomous Robots, etc. within the classic Sci-Fi film 2001: an area Odyssey, HAL is an intelligent conversational platform which will take decisions without human interference.
These things are not any longer works of fiction anymore. With the emergence of tongue Processing and Reinforcement Learning, it’s now possible to create such platforms within the times. While it’s true that the sector of knowledge Science is immense, its rewards, however, are even greater. As technologies are rapidly evolving and changing, new technologies are replacing the older ones.
As a result, we’d like to be dynamic, continue with technology and keep moving forward. Therefore, it’s the necessity of the hour to find out Data Science and build a successful career within the future.
From the above article, we learn that Data Science has transformed our society. Data Science gives meaning to data. It converts crude data into meaningful products that can be used by industries to generate insights and recognize market trends. With a dearth in the supply of specialized Data Scientists and a rapid increase in demand, there is a huge income bubble that has made Data Science a lucrative career. Here we conclude that learning Data Science is the hour of need and we must be data-literate to take up jobs of the future