The current wave of digitization has given a new lease of life to various digital applications and systems. Data is rightly recognized as the oil and currency in this new digital ecosystem. It is further believed that the future economy will give a boost to the data science economy. It is in this context that private and public sectors are significantly investing in digital products to keep up with this change in the digital market. As such, the people are also reacting to, reflecting upon, and revisiting the skills that can enable them to thrive in this digital economy. People are exploring their options of various certifications in data science and this is becoming a trend both in the academic and industrial domains. The levels of innovation that we are seeing in the digital market have been sourced from data that acts as a raw material for all digital change and transformation.
The contours of digital change and transformation
Digital change is a result of the growing importance of data in the age of industry 4.0. The fourth Industrial Revolution has led to a significant transformation in the roles and skills of the present workforce. As such, there has been a constant shift in the data market as well as the information technology market. The sub-sectors that have been most influenced by the rapid digital transformation include financial services, media, and professional services. It needs to be noted at this point in time that the changing contours of digital change have led to the emergence of new roles like machine learning engineer, data scientist, data analyst as well as relationship consultants. In addition to this, other types of roles are also popping up in the data market as a result of rapid digital transformation. Jobs in the sectors of Artificial Intelligence and machine learning have been proposed to occupy the center stage in the next few years. Credit goes to the ability of data scientists and machine learning engineers to crunch large volumes of data and visualize it in a format that is easily understandable to users. The industrial insights that are derived from the large data sets are helping businesses to penetrate new markets and widen their range of products. Various types of data management systems have led to effective innovation mechanisms that have directly or indirectly led to the optimization of business operations.
Industrial impact of data science
Data science has greatly impacted large industrial sectors as these sectors have been increasingly driven by information in the age of the data economy. It is important to analyze the extent of growth that the industrial sectors have witnessed as a result of data processing and management capabilities in the last five years. The statistics that we mention here have been sourced from a report of the world economic forum titled Data Science in the new economy. The highest growth has been witnessed in the domain of information communication and technology which is of the order of about 60%. In the domain of media and entertainment, there has been more than 50% growth in the last 5 years due to the adoption of data-based services. Similarly, the financial sector, the investment sector, and the retail sector have shown a joint growth of more than 80% as an aggregate. The advertisement industry has seen a growth of about 75% while the growth in the E-Commerce industry has been about 66%. When we take a look at the education and healthcare services, we find the growth rate in these domains to be 50% and 35% respectively. Finally, the growth rates in the domain of aviation, travel, tourism, mining and metals, biotechnology, infrastructure, energy, and chemical industry have been 20%, 18%, 12%, 42%, 67%, and 32% respectively.
Future belongs to the data economy
Given the exponential growth in the data market and the number of sectors that have been impacted due to data, we may conclude that the future rightly belongs to the data economy. This economy that would be driven by Big Data Analytics would focus on innovation and growth through the lens of data science. Priority in the data economy would be given to the reskilling of individuals, upskilling of the workforce, and reorientation of policymakers. Furthermore, various types of stakeholders will be roped in to sketch the future roadmap of innovation and growth in the data economy.
