Data Science and Predictive Analytics Market size was over USD 19.07 billion in 2024 and is projected to reach USD 179.05 billion by 2037, witnessing around 18.8% CAGR during the forecast period i.e., between 2025-2037. In the year 2025, the industry size of data science and predictive analytics is assessed at USD 25.24 billion.
The continuous improvement in global internet connectivity and countless technical developments, among other things, have greatly accelerated economic growth during the past two decades. There were more than 4.5 billion persons actively utilizing the Internet as of April 2021 across the globe.
Additionally, the ICT sector's creation of goods and services boosts economic growth and development. According to data in the database of the United Nations Conference on Trade and Development, the worldwide exports of ICT goods increased from 10.816 % in 2015 to 11.536 % in 2019.
Growth Drivers
Challenges
Base Year |
2024 |
Forecast Year |
2025-2037 |
CAGR |
18.8% |
Base Year Market Size (2024) |
USD 19.07 billion |
Forecast Year Market Size (2037) |
USD 179.05 billion |
Regional Scope |
|
Component (Solutions, Services)
With a 58% revenue share during the anticipated period, the solution sector leads the data science and predictive analytics market growth. The market for data science and predictive analytics has a sizable section dedicated to the solution. Analytics pertaining to customers, networks, risks, finances, marketing, supply chains, online and social media, and other areas. This technology offers analytical answers for the whole of this category. These solutions are developed using data from an existing source, and after analysis, the customer receives a specific number to move on.
Application (Financial Risk Analysis, Marketing & Sales Analysis, Customer Analysis, Supply Chain Analytics)
The customer analytics sector is expected to hold 30% share of the global data science and predictive analytics market in the near future. Customer intelligence is a systematic and sophisticated analytical method that businesses are increasingly using to analyse consumer behaviour. Businesses utilize this information to improve their total income creation and make critical business decisions. Additionally, customer analytics, which includes methods like predictive modelling and data visualisation, aids businesses in boosting customer lifetime value (CLV), winning over new clients, and keeping hold of current ones. The customer analysis market, which was valued at USD 6.25 in 2018, is anticipated to increase at a CAGR of 19.34% from 2023 to 2030, reaching USD 30.69 billion.
Our in-depth analysis of the global market includes the following segments:
Component |
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Application |
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North American Market Forecast
North America industry is estimated to dominate majority revenue share of 35% by 2037. In comparison to other areas, North America is predicted to have the greatest rate of adoption of predictive analytics solutions. The fact that several industrialized nations, like Canada and the US, are present in this region is the key factor influencing the rising adoption rate. It is an economically robust, technologically developed area. As a result, there is a high rate of adoption of cutting-edge technology, which contributes to the market expansion in the North American area. Additionally, during the anticipated period, the market for data science and predictive analytics would grow due to advancements in new developing technologies and R&D carried out by solution-providing firms in this area.
European Market Statistics
The Europe data science and predictive analytics market is projected to be 28%. The main element influencing the market expansion in this area is the presence of significant major players and the high adoption rate of data science and predictive analytics solutions. In addition, this region's healthcare and life sciences industry is flourishing because of its robust economy, infrastructure, and R&D activities. The healthcare and life sciences industries produce a large amount of data. The use of digital technologies such as big data, and predictive analytics, which gather, process, and aid to sustain hospital performance, creates enormous amounts of information that are very difficult for older technologies to handle.
Author Credits: Abhishek Verma
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