Globally, data is becoming the most valuable resource for making better-informed decisions. Various organizations from multinational companies to start-ups rely on survey-based data that provide deeper insights into the preferences of their customers allowing them to target the right audience. Hence, it is of no surprise that there is an abundance of job opportunities for data scientists at present and the demand will continue to increase in the future.
Data scientists identify correlated questions, extricate information from the sources, compile the information and convert end results into solutions. To put it simply, data science is the ability to make data understandable and processable so it can improve its quality.
Data scientists need to have expertise in a wide range of fields such as mathematical computation, statistics, AI, Machine learning, modelling and even programming languages such as Python, Pig, Hadoop, SQL, and more.
Top future leaders of Data Science:
Telecommunication: Telecommunication industry utilises big data analytics to optimize network usage and services, improve user’s experience and enhance security that in turn helps them in huge profit making and planning efficient market strategies. This sector also uses information taken from their devices to carry out predictive analytics for better data-driven decision-making. Machine learning algorithms are used to detect unusual user activity which helps in fraud detection or fraud prevention.
E-commerce: There is an increasing need for extensive data evaluation in the E-commerce and retail sectors. Information Analytics help e-commerce businesses forecast sales, profits and losses by monitoring, capturing and integrating customer web activities and influencing users into buying products. In the same way, retailers analyze profiles of clients and in accordance with their findings, promote products that will entice customers to buy.
Banking: Information technology is among the foremost tool used by Banking sector to improve procedures and safety. Technology is helping banks to understand their clients better, retain them, and attract fresh clients. Using data analytics, banks are able to engage with customers more effectively by determining activity habits of the customers. The accessible information on transactions helps in the prevention of fraud and risks.
Manufacturing: Data Science caters to several needs in the manufacturing industry. Using Warranty analytics and artificial intelligence, manufacturers can produce large volumes of data related to warranties from a variety of sources and find warranty-related issues. Data scientists utilise DS analytics to manage supply chain risks. Data Science helps improve efficiency, maximise profits and streamline operations.
Healthcare: Data from daily activities like medical records, accounting, clinical services, information via health trackers, and other sources generate massive amounts of data. Data scientists utilise data analytics to get useful insights on patients data.
HR: Data analytics is often deployed to help HR professionals make more informed decisions about the future of their workforce. Human resource management, often known as people data, is the study of social issues and the application of information to answer crucial questions about your company.