August 31, 2018 by
During the last couple of years, data science has grown at an exponential rate. As per industry experts, it will keep on growing in the coming years and will improve significantly. If you are planning to make a career in the IT sector then this would be the best option for you. To make the career as a data scientist can be one of the best options for you.
Virtually big data is part of every organization especially for those that are involved in data. Such organizations need data scientists that must know the way to use the skills of mathematics, statistics, programming and other related specialization. The data scientists take their decisions based on the data.
In this article, we will discuss the Data Science profession and the reasons due to which one should learn this innovative and beneficial technology.
Before we dive deep into the topic, let us first learn What is Data Science and why is it so helpful for business organizations. After this, we will discuss the top 7 reasons why someone should practice data science in 2018.
Introduction to Data Science
The need for data storage has been increased with the growth of the amount of data that is present throughout the internet. The main and biggest challenge in front of organizations was to store and analyze the data so that they can use it efficiently and they are also worried about data processing along with storing it. This is where data science helped them. Data science is known as the future of artificial intelligence.
Now if you want to know what data science is then it is a blend of various algorithms, tools, and machine learning principles. The goal of data science is to discover the hidden pattern behind the raw data. This is not like the traditional statistics and is able to take smart and precise decisions. Professionals that are associated with the data science field are known as data scientists.
Data scientists not only do a detailed analysis to find the insights of data, instead, they also use a number of advanced machine learning algorithms to identify any particular pattern or information from raw data. So data science is also known as predictive analysis that is used to take decisions and make predictions. Below listed analysis can be performed by the data scientists:
  • Predictive Casual Analytics
  • Prescriptive Analytics
  • Machine Learning for making predictions
  • Machine learning for pattern discovery
Many times even business intelligence is misunderstood as data science. In fact, these are two separate fields and are not similar. Where business intelligence usually takes data from history and various internal and external source, so on the other hand data science is a forward approach and is able to analyze current and past data. The aim of the data science is to take informed decisions.
Reasons to Learn Data Science
You may wonder that why should I learn Data science, so here we are going to discuss and enlist all possible reasons due to which you should learn data science:
  • Data Science and Analysis is Priority for All Organizations
In this competitive era and the growing amount of quantity of data organizations are turning to data analytics so that they can identify the market trends and new opportunities for their service or product. Today more than 77% of organizations are considering data analytics as a critical business component. It signifies that big data or data science professionals have a huge influence on the marketing strategies of the Company and are an important part of the organizations.
  • Many Job Opportunities
The organizations know that they do not have skilled professionals to gather, interpret and use data, so they are hiring the specialists who can easily do it. The number of requirements, therefore, is increasing day by day on popular job search sites like indeed. Many companies are looking for data scientists and analysts for them. Even the demand of such professionals is higher than the supply. Therefore, the number of opportunities is increasing for such professionals.
  • Better salary is offered to Data Science professionals
As the supply of skilled data science professionals is lower so the professionals are getting a better salary. These professionals are paid 50% better salary than their counterparts in other IT fields with similar experience. Across the globe, they are offered better salaries as the organizations are realizing the worth of these professionals.
  • Big Data and Data Science is Present Everywhere
As today computer is being used at every workplace, so the need of data science professionals is also there in every organization. Practically there is no sector that has been untouched for data science or data analysis. Big data is present everywhere and in every type of organization.
  • Part of Decision-Making Teams
Being a data scientist, you will be an essential part of the decision-making team. It has been noticed that in many organizations employees feel that they have no decision making power in their organization, but as a data science professional you will become an integral part of the organization and will be able even to form the attractive strategies for your organization. So you will get an important role and purpose of the organization.
  • Many Freelancing Opportunities Are Available
In the nearby future, a number of data scientists will no remain tied to a single organization. People will adopt diversified ways to get the better salary and to have work-life balance. Data science can give you the perfect opportunities and, in this way, the professionals can do the job anywhere in the world.
  • A New Stream of Revenue
The ability to organize and putting the data intelligently you can identify new ways to generate the revenues. By learning the data science technology you can increase your earnings and even adopt it as your additional source of income.
Final Words
It can be said that the demand for data science professionals is rising continuously. Soon it will be an essential part of every organization. So, you can easily understand how important is data science for your profession.
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