Data Science in 21st Century

The word data science itself makes us understand what data science means. It is related to big data. There are many learning concepts and tools such as artificial intelligence, machine learning, algorithms in data science. Machine learning is the heart of data science. Data Science is one of the top trending technology of the era and data science has stretched its roots deep down in the corporate industry. Due to this vast inference, new age learners and working professionals are keen to learn this technology. To curb this, various online data science courses are available through which one can master data science and begin career as a data scientist.
Data science is a broad career path and is undergoing developments and thus promises abundant opportunities in the future. Data Science job roles are likely to get more specific, which will lead to specializations in the field. People inclined towards this
stream can exploit their opportunities and pursue what suits them best through there specializations and specifications. This article will let you know about data science and why we need data science.

Introduction

As we entered into the modern era of big data, there is a need for storage growth. The main use of data science is to build frameworks and solutions to store data. It is very important to understand what data science is and how it can help us. Let’s go deeper and observe how data science is being in various domains.

• Let’s take sedimentation in rivers, canals as an example. Every year due to increase in sediment under rivers there is no proper control of floods, irrigation, power generation etc. The efficiency of dams, rivers, canals has been decreased. The solution for this problem can be solved by data science concepts. Take rainfall, temperature as inputs. Past and present values of sediment load will be collected and observed to build models. These help in predicting the future sediment load and we can take natural measures to avoid sediment formation.
• Let’s take automotive vehicles. This is a vehicle to vehicle communication. It doesn’t need any human interaction to work. The vehicle itself has to collect the data from sensors such as cameras, signals, and to create a map on its surroundings. By the collected data ,the vehicle itself decides the speed according to the traffic and when to make a turn. By using machine learning algorithms , automotive vehicles can be developed.
• There are many domains where there is use of data science such as credit and insurance, healthcare, travel, marketing, social media, weather forecasting etc. As these domains contain huge data to store , there is a need for data science.

Conclusion

Data science consists of many tools, algorithms, and machine learning concepts to achieve the hidden data from present and past data . The present era is dependent on big data analysts and the future era will completely depend on data scientists. At the end of the year , there will be a need for many data scientists as a lot of data will be provided to run the business decisions. Data science can change the shape of the world by solving the most complex problems. Also, check for python data science course and learn how to apply concepts of python with data science.