Data has caused a virtual explosion of information around us. Data is constantly transforming our world like never before. For a very strong reason, data has been the oil as well as the currency and oxygen of the 21st century.
When we look at the progress of data science, we find that it has really made a mark and changed technology in the last ten years. From the inception of this technology to its maturity, data science has transformed various spheres like never before. By leveraging the power of data science, businesses are entering a new phase of growth, research, and development. Consequently, in this age of digital convergence, data science certifications are serving as a passport to enter the new job market that has been created by a unique currency of data.
The technological giants like Amazon and Facebook have set up dedicated centres of data science research in order to reap the potential of this technology to its fullest.
Article highlights
In this article, we understand the relevance of data science for various sectors that are directly or indirectly dependent on data. We then move on to understand the rising demand for data scientists and also suggest measures to cope up with this demand as data science continues to undergo further extension. After this, we examine how the entry of artificial intelligence has widened the horizons of data science. Finally, we conclude by relating the growth of big data technology to the growth of data-dependent businesses globally.
Relevance of data science to different sectors
The relevance of data science to various sectors can be understood from the interdisciplinary nature of the subject. As per The Economist, the field of data science combines various types of skills like programming, statistics, mathematics, storytelling, business analytics and data mining with the prime motive of deriving insights and uncovering hidden facts.
It is due to the interdisciplinary nature of the subject of data science that it is relevant to numeral sectors. Some of these sectors include education, healthcare, tourism, mining, industry, navigation, transportation, satellite imaging, logistics, real estate, stock market, financial services, e-commerce and the like.
Rising demand for data scientists
The demand for data scientists is constantly increasing. By the end of 2025, the demand for data scientists will have increased to more than 150% of what it is today. This demand can be attributed to three important factors. The first is the relevance of data science to a wide range of sectors. The second important factor is the degree of automation that is being carried out in various sectors and the dependency on data that is being created. The third important sector is the orientation of different businesses towards data driven decisions as well as data driven insights.
Measures to cope up with the demand
There is no doubt in the fact that we have to cope up with the growing demand of data scientists. We need to prioritize data science courses as well as data science training on a large scale. It is also important that we re-skill our existing workforce and also make certain changes at the infrastructural level.
Incubation centres may be started that help in the nurturing of startups while simultaneously imparting critical skills to data scientists. As the scope of data science is very large and vast, it is extremely important that sector specific skills be imparted to data scientists.
For instance, data scientists who need to work with developers can be imparted programming skills in C, Python and Java. Similarly, data scientists who need to work at the front end need to be given related skills. The data scientists who need to work with a digital marketing team need to be given skills related to analytics. Those data scientists that need to deal with business operations and expansion of a business need to be imparted skills related to data driven decision making.
So, we conclude that data scientists need to operate in an interdisciplinary medium. Consequently, it is pertinent that they should be imparted a wide range of skills that enable them to take up numerous tasks in a variety of domains.
AI widening the horizons of data science
Since data science is a very vast field, its horizons were further widened with the incorporation of Artificial Intelligence and machine learning in its domain. The entry of artificial intelligence made it possible for scaling of AI driven software projects in a short span of time. In addition to this, a lot of innovations also began to materialize with the advent of artificial intelligence and big data technology under the umbrella of data science. Some of the examples of the progress achieved include self driving cars, internet of things, speech recognition apps and chatbots.
Companies also started to experiment with core AI technology by incorporating it into various products and services. Data science made it possible to scale up the AI technology used in different products and services. Consequently, data science played the role of commercialisation of this high-tech technology. Another effective achievement was the cost effective nature of various products and services that made them feasible and affordable for a large audience worldwide.
Big Data Technologies culminate into growth of businesses
Big data technologies play a great role in driving the growth of businesses in one way or the other. In the present time, a lot of businesses are becoming data dependent and data driven. When a business harnesses big data technology to derive effective insights, it becomes possible to target the right customers with the right genre of products. Big data technology also enables the growth of a business by providing effective insights as well as by enhancing quantitative analytics. With the help of effective analytics, businesses can sketch the road map for their future growth.
The bottom line
Data science has taken various businesses from the juvenile stage to the stage of maturity in a span of just ten years. It would not be an exaggeration to say that data science has made businesses self-sufficient in nature. Data science has driven businesses to a stage from where it is impossible to beat a retreat.
