The evolution of data science and its changing role

It is impossible to predict what the future holds when it comes to technology and its evolution. Over time, there has been a great deal of demand for technologies that would aid in managing data. The term “Data Science” came to light in the past few years to make it easier to understand the underlying work related to data. Data science technology initially involved statistical analysis only. Eventually, it adopted new-age technologies such as artificial intelligence (AI), machine learning (ML), and data mining. Data science is a constantly evolving technology with enormous potential to bring about massive improvements in the future.

The future of data science

In recent years, we witnessed the introduction of data-driven technologies and the popularity of technologies like ML, AI, and cloud computing. ML and AI dominate the future of technology. Data scientists around the globe are engaged in learning and developing innovative methods to make computers smarter. The technological world is pointing towards a future of extensively automated industries.

Data science: What changes will it bring in the next decade?

The field of data science is considered to have emerged in 2010. Since then, there have been simultaneous changes in technology. Several innovations and approaches have been introduced to solve the problems related to data and its management.

Let’s have a look at what the future of data science will look like.

Automation in Data Science

The recent technological advancements in ML and AI will call forth automation in data science. Automated machine learning pipelines are already being used to streamline the tedious processes in data science.

Data generation from IoT

A significant amount of data is expected to be generated by the Internet of Things compared to the internet today, leading to data scientists having access to all types of data. IoT will bring about a noticeable change in data science and the efforts of data scientists.

Changes in data visualisation and Virtual Reality

Currently, data visualisation plays a key role in business operations and decision-making. A new generation of immersive data experiences will be created by combining data visualisation with technologies like Virtual Reality (VR) and Augmented Reality (AR).

This list of three possibilities may not be comprehensive of all the possibilities in the field of data science. We’ll now look at the scope of a data scientist.

Scope of a Data Scientist

Now, data science is one of the most in-demand technologies. The same is true for data scientists. The need for a highly skilled workforce will be in demand as long as data exists. The role of data scientists is equally important to that of data analysis and analytic tools. The tremendous amount of data demands the need of skilled professionals to analyse and manage it in the right way, favourable for better decision making.

Conclusion

Data Science technology is expected to bring about massive changes in the next decade. Customer experience and business intelligence have been revolutionised by data science. The field of data science continues to evolve rapidly, offering tremendous potential for future improvements. 

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