Data Science and Predictive Analytics Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Deployment, By Enterprise Type, By Application, By End User, By Region & Competition, 2021-2031F

Description

The Global Data Science and Predictive Analytics Market is projected to grow from USD 19.54 Billion in 2025 to USD 71.34 Billion by 2031, registering a CAGR of 24.09%. This market is defined as the sector comprising advanced software platforms and statistical methodologies utilized to extract actionable insights and forecast future outcomes from complex datasets. The primary drivers propelling this market include the exponential growth in enterprise data volume and the critical necessity for real-time business intelligence to optimize operational efficiency, while the increasing accessibility of scalable cloud infrastructure supports these drivers by reducing entry barriers for organizations seeking to leverage high-performance analytical tools.

Market Overview
Forecast Period	2027-2031
Market Size 2025	USD 19.54 Billion
Market Size 2031	USD 71.34 Billion
CAGR 2026-2031	24.09%
Fastest Growing Segment	Small and Medium Enterprises (SMEs)
Largest Market	North America

However, the industry faces a significant challenge regarding the acute shortage of skilled talent required to develop and manage these sophisticated systems. According to the Computing Technology Industry Association (CompTIA), in 2024, the employment demand for data scientists and analysts was projected to expand by approximately 35 percent over the next decade, a rate significantly outpacing the broader labor market. This persistent skills gap creates a bottleneck that restricts the effective deployment of predictive models and hampers the potential pace of market expansion globally.

Market Driver

The deep integration of Artificial Intelligence and Machine Learning technologies fundamentally transforms the capabilities of analytics platforms, shifting the focus from historical reporting to forward-looking foresight. Modern algorithms now automate complex data processing tasks, allowing organizations to ingest unstructured datasets and generate predictive models with unprecedented speed and accuracy. This technological convergence is critical for enterprises aiming to operationalize generative models within their analytical workflows, a trend supported by IBM's January 2024 'Global AI Adoption Index 2023', which noted that 42 percent of enterprise-scale organizations have actively deployed AI in their business, fueling the requirement for advanced data science tools capable of managing these intelligent workflows.

Concurrently, the rising adoption of cloud-based analytical infrastructures acts as a necessary foundation for processing the massive datasets required for these accurate predictions. Cloud environments offer the elastic scalability and computational power needed to run resource-intensive algorithms without the prohibitive capital expenditure of on-premise hardware, facilitating real-time collaboration and democratizing access to high-performance computing resources. According to Flexera's '2024 State of the Cloud Report' from March 2024, 51 percent of organizations reported heavy usage of public cloud, a robust environment further evidenced by Microsoft's 2024 pledge to invest 3.3 billion EUR in Germany to expand its artificial intelligence and cloud center capacity.

Market Challenge

The scarcity of skilled professionals represents a critical impediment to the growth of the Global Data Science and Predictive Analytics Market. Although organizations possess vast amounts of data and access to advanced analytical platforms, the lack of qualified personnel capable of interpreting complex datasets restricts the successful deployment of these technologies. This talent gap leads to project delays, increased operational costs, and a failure to fully realize the return on investment from analytics initiatives, forcing many enterprises to scale back their digital strategies and slowing the adoption rate of predictive software.

This bottleneck is substantiated by recent industry data regarding workforce readiness. According to the World Economic Forum, in 2025, 63 percent of employers identified skills gaps as the primary barrier to business transformation. This specific deficiency in technical proficiency prevents companies from effectively integrating predictive models into their core operations, resulting in a structural limitation where the availability of human capital lags behind technological capability and restricting the industry's potential for rapid global expansion.

Market Trends

The operationalization of models through MLOps and DataOps practices is reshaping the market by establishing standardized frameworks for the lifecycle management of predictive algorithms. As organizations move beyond experimental pilots, the focus shifts toward robust engineering pipelines that ensure model reproducibility, continuous monitoring, and automated retraining in production, addressing the historic failure rate where successful prototypes failed to scale or degraded due to data drift. The acceleration of this trend is evident in recent deployment metrics; according to Databricks' 'State of Data + AI 2024' report from June 2024, the number of machine learning models put into production by enterprises grew by 411 percent year-over-year, highlighting a decisive move from ad-hoc analysis to integrated, value-generating operational workflows.

Simultaneously, the market is shifting toward real-time and streaming data analytics, driven by the need for immediate responsiveness in dynamic business environments. Traditional batch processing, which analyzes historical data at set intervals, is being supplemented by event-driven architectures that process information as it is generated, allowing predictive systems to ingest high-velocity data for instantaneous decisions. The strategic importance of this capability is increasingly recognized by technology decision-makers; according to Confluent's '2024 Data Streaming Report' from June 2024, 86 percent of IT leaders cited data streaming as a top strategic or important priority for IT investments in 2024, confirming that businesses are prioritizing the ability to harness data in motion for competitive advantage.

Key Market Players

Accenture plc
Vention, Inc.
Absolutdata Analytics Pvt. Ltd.
Salesforce, Inc.
Manthan Software Services Pvt. Ltd.
LatentView Analytics Private Limited
Oracle Corporation
SG Analytics, Inc.
Mu Sigma Inc.
Fractal Analytics Private Limited

Report Scope

In this report, the Global Data Science and Predictive Analytics Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Data Science and Predictive Analytics Market, By Component

Solution
Service

Data Science and Predictive Analytics Market, By Deployment

Cloud
On-premise

Data Science and Predictive Analytics Market, By Enterprise Type

Large Enterprises
Small
Medium Enterprises (SMEs)

Data Science and Predictive Analytics Market, By Application

Financial Risk Analysis
Marketing & Sales Analysis
Customer Analysis
Supply Chain Analytics

Data Science and Predictive Analytics Market, By End User

BFSI
Automotive
IT & Telecom
Healthcare
Retail
Energy & Utility
Government
Others

Data Science and Predictive Analytics Market, By Region

North America
- United States
- Canada
- Mexico
Europe
- France
- United Kingdom
- Italy
- Germany
- Spain
Asia Pacific
- China
- India
- Japan
- Australia
- South Korea
South America
- Brazil
- Argentina
- Colombia
Middle East & Africa
- South Africa
- Saudi Arabia
- UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Data Science and Predictive Analytics Market.

Available Customizations:

Global Data Science and Predictive Analytics Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

1. Product Overview

1.1. Market Definition
1.2. Scope of the Market
- 1.2.1. Markets Covered
- 1.2.2. Years Considered for Study
- 1.2.3. Key Market Segmentations

2. Research Methodology

2.1. Objective of the Study
2.2. Baseline Methodology
2.3. Key Industry Partners
2.4. Major Association and Secondary Sources
2.5. Forecasting Methodology
2.6. Data Triangulation & Validation
2.7. Assumptions and Limitations

3. Executive Summary

3.1. Overview of the Market
3.2. Overview of Key Market Segmentations
3.3. Overview of Key Market Players
3.4. Overview of Key Regions/Countries
3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Data Science and Predictive Analytics Market Outlook

5.1. Market Size & Forecast
- 5.1.1. By Value
5.2. Market Share & Forecast
- 5.2.1. By Component (Solution, Service)
- 5.2.2. By Deployment (Cloud, On-premise)
- 5.2.3. By Enterprise Type (Large Enterprises, Small, Medium Enterprises (SMEs))
- 5.2.4. By Application (Financial Risk Analysis, Marketing & Sales Analysis, Customer Analysis, Supply Chain Analytics)
- 5.2.5. By End User (BFSI, Automotive, IT & Telecom, Healthcare, Retail, Energy & Utility, Government, Others)
- 5.2.6. By Region
- 5.2.7. By Company (2025)
5.3. Market Map

6. North America Data Science and Predictive Analytics Market Outlook

6.1. Market Size & Forecast
- 6.1.1. By Value
6.2. Market Share & Forecast
- 6.2.1. By Component
- 6.2.2. By Deployment
- 6.2.3. By Enterprise Type
- 6.2.4. By Application
- 6.2.5. By End User
- 6.2.6. By Country
6.3. North America: Country Analysis
- 6.3.1. United States Data Science and Predictive Analytics Market Outlook
  - 6.3.1.1. Market Size & Forecast
    - 6.3.1.1.1. By Value
  - 6.3.1.2. Market Share & Forecast
    - 6.3.1.2.1. By Component
    - 6.3.1.2.2. By Deployment
    - 6.3.1.2.3. By Enterprise Type
    - 6.3.1.2.4. By Application
    - 6.3.1.2.5. By End User
- 6.3.2. Canada Data Science and Predictive Analytics Market Outlook
  - 6.3.2.1. Market Size & Forecast
    - 6.3.2.1.1. By Value
  - 6.3.2.2. Market Share & Forecast
    - 6.3.2.2.1. By Component
    - 6.3.2.2.2. By Deployment
    - 6.3.2.2.3. By Enterprise Type
    - 6.3.2.2.4. By Application
    - 6.3.2.2.5. By End User
- 6.3.3. Mexico Data Science and Predictive Analytics Market Outlook
  - 6.3.3.1. Market Size & Forecast
    - 6.3.3.1.1. By Value
  - 6.3.3.2. Market Share & Forecast
    - 6.3.3.2.1. By Component
    - 6.3.3.2.2. By Deployment
    - 6.3.3.2.3. By Enterprise Type
    - 6.3.3.2.4. By Application
    - 6.3.3.2.5. By End User

7. Europe Data Science and Predictive Analytics Market Outlook

7.1. Market Size & Forecast
- 7.1.1. By Value
7.2. Market Share & Forecast
- 7.2.1. By Component
- 7.2.2. By Deployment
- 7.2.3. By Enterprise Type
- 7.2.4. By Application
- 7.2.5. By End User
- 7.2.6. By Country
7.3. Europe: Country Analysis
- 7.3.1. Germany Data Science and Predictive Analytics Market Outlook
  - 7.3.1.1. Market Size & Forecast
    - 7.3.1.1.1. By Value
  - 7.3.1.2. Market Share & Forecast
    - 7.3.1.2.1. By Component
    - 7.3.1.2.2. By Deployment
    - 7.3.1.2.3. By Enterprise Type
    - 7.3.1.2.4. By Application
    - 7.3.1.2.5. By End User
- 7.3.2. France Data Science and Predictive Analytics Market Outlook
  - 7.3.2.1. Market Size & Forecast
    - 7.3.2.1.1. By Value
  - 7.3.2.2. Market Share & Forecast
    - 7.3.2.2.1. By Component
    - 7.3.2.2.2. By Deployment
    - 7.3.2.2.3. By Enterprise Type
    - 7.3.2.2.4. By Application
    - 7.3.2.2.5. By End User
- 7.3.3. United Kingdom Data Science and Predictive Analytics Market Outlook
  - 7.3.3.1. Market Size & Forecast
    - 7.3.3.1.1. By Value
  - 7.3.3.2. Market Share & Forecast
    - 7.3.3.2.1. By Component
    - 7.3.3.2.2. By Deployment
    - 7.3.3.2.3. By Enterprise Type
    - 7.3.3.2.4. By Application
    - 7.3.3.2.5. By End User
- 7.3.4. Italy Data Science and Predictive Analytics Market Outlook
  - 7.3.4.1. Market Size & Forecast
    - 7.3.4.1.1. By Value
  - 7.3.4.2. Market Share & Forecast
    - 7.3.4.2.1. By Component
    - 7.3.4.2.2. By Deployment
    - 7.3.4.2.3. By Enterprise Type
    - 7.3.4.2.4. By Application
    - 7.3.4.2.5. By End User
- 7.3.5. Spain Data Science and Predictive Analytics Market Outlook
  - 7.3.5.1. Market Size & Forecast
    - 7.3.5.1.1. By Value
  - 7.3.5.2. Market Share & Forecast
    - 7.3.5.2.1. By Component
    - 7.3.5.2.2. By Deployment
    - 7.3.5.2.3. By Enterprise Type
    - 7.3.5.2.4. By Application
    - 7.3.5.2.5. By End User

8. Asia Pacific Data Science and Predictive Analytics Market Outlook

8.1. Market Size & Forecast
- 8.1.1. By Value
8.2. Market Share & Forecast
- 8.2.1. By Component
- 8.2.2. By Deployment
- 8.2.3. By Enterprise Type
- 8.2.4. By Application
- 8.2.5. By End User
- 8.2.6. By Country
8.3. Asia Pacific: Country Analysis
- 8.3.1. China Data Science and Predictive Analytics Market Outlook
  - 8.3.1.1. Market Size & Forecast
    - 8.3.1.1.1. By Value
  - 8.3.1.2. Market Share & Forecast
    - 8.3.1.2.1. By Component
    - 8.3.1.2.2. By Deployment
    - 8.3.1.2.3. By Enterprise Type
    - 8.3.1.2.4. By Application
    - 8.3.1.2.5. By End User
- 8.3.2. India Data Science and Predictive Analytics Market Outlook
  - 8.3.2.1. Market Size & Forecast
    - 8.3.2.1.1. By Value
  - 8.3.2.2. Market Share & Forecast
    - 8.3.2.2.1. By Component
    - 8.3.2.2.2. By Deployment
    - 8.3.2.2.3. By Enterprise Type
    - 8.3.2.2.4. By Application
    - 8.3.2.2.5. By End User
- 8.3.3. Japan Data Science and Predictive Analytics Market Outlook
  - 8.3.3.1. Market Size & Forecast
    - 8.3.3.1.1. By Value
  - 8.3.3.2. Market Share & Forecast
    - 8.3.3.2.1. By Component
    - 8.3.3.2.2. By Deployment
    - 8.3.3.2.3. By Enterprise Type
    - 8.3.3.2.4. By Application
    - 8.3.3.2.5. By End User
- 8.3.4. South Korea Data Science and Predictive Analytics Market Outlook
  - 8.3.4.1. Market Size & Forecast
    - 8.3.4.1.1. By Value
  - 8.3.4.2. Market Share & Forecast
    - 8.3.4.2.1. By Component
    - 8.3.4.2.2. By Deployment
    - 8.3.4.2.3. By Enterprise Type
    - 8.3.4.2.4. By Application
    - 8.3.4.2.5. By End User
- 8.3.5. Australia Data Science and Predictive Analytics Market Outlook
  - 8.3.5.1. Market Size & Forecast
    - 8.3.5.1.1. By Value
  - 8.3.5.2. Market Share & Forecast
    - 8.3.5.2.1. By Component
    - 8.3.5.2.2. By Deployment
    - 8.3.5.2.3. By Enterprise Type
    - 8.3.5.2.4. By Application
    - 8.3.5.2.5. By End User

9. Middle East & Africa Data Science and Predictive Analytics Market Outlook

9.1. Market Size & Forecast
- 9.1.1. By Value
9.2. Market Share & Forecast
- 9.2.1. By Component
- 9.2.2. By Deployment
- 9.2.3. By Enterprise Type
- 9.2.4. By Application
- 9.2.5. By End User
- 9.2.6. By Country
9.3. Middle East & Africa: Country Analysis
- 9.3.1. Saudi Arabia Data Science and Predictive Analytics Market Outlook
  - 9.3.1.1. Market Size & Forecast
    - 9.3.1.1.1. By Value
  - 9.3.1.2. Market Share & Forecast
    - 9.3.1.2.1. By Component
    - 9.3.1.2.2. By Deployment
    - 9.3.1.2.3. By Enterprise Type
    - 9.3.1.2.4. By Application
    - 9.3.1.2.5. By End User
- 9.3.2. UAE Data Science and Predictive Analytics Market Outlook
  - 9.3.2.1. Market Size & Forecast
    - 9.3.2.1.1. By Value
  - 9.3.2.2. Market Share & Forecast
    - 9.3.2.2.1. By Component
    - 9.3.2.2.2. By Deployment
    - 9.3.2.2.3. By Enterprise Type
    - 9.3.2.2.4. By Application
    - 9.3.2.2.5. By End User
- 9.3.3. South Africa Data Science and Predictive Analytics Market Outlook
  - 9.3.3.1. Market Size & Forecast
    - 9.3.3.1.1. By Value
  - 9.3.3.2. Market Share & Forecast
    - 9.3.3.2.1. By Component
    - 9.3.3.2.2. By Deployment
    - 9.3.3.2.3. By Enterprise Type
    - 9.3.3.2.4. By Application
    - 9.3.3.2.5. By End User

10. South America Data Science and Predictive Analytics Market Outlook

10.1. Market Size & Forecast
- 10.1.1. By Value
10.2. Market Share & Forecast
- 10.2.1. By Component
- 10.2.2. By Deployment
- 10.2.3. By Enterprise Type
- 10.2.4. By Application
- 10.2.5. By End User
- 10.2.6. By Country
10.3. South America: Country Analysis
- 10.3.1. Brazil Data Science and Predictive Analytics Market Outlook
  - 10.3.1.1. Market Size & Forecast
    - 10.3.1.1.1. By Value
  - 10.3.1.2. Market Share & Forecast
    - 10.3.1.2.1. By Component
    - 10.3.1.2.2. By Deployment
    - 10.3.1.2.3. By Enterprise Type
    - 10.3.1.2.4. By Application
    - 10.3.1.2.5. By End User
- 10.3.2. Colombia Data Science and Predictive Analytics Market Outlook
  - 10.3.2.1. Market Size & Forecast
    - 10.3.2.1.1. By Value
  - 10.3.2.2. Market Share & Forecast
    - 10.3.2.2.1. By Component
    - 10.3.2.2.2. By Deployment
    - 10.3.2.2.3. By Enterprise Type
    - 10.3.2.2.4. By Application
    - 10.3.2.2.5. By End User
- 10.3.3. Argentina Data Science and Predictive Analytics Market Outlook
  - 10.3.3.1. Market Size & Forecast
    - 10.3.3.1.1. By Value
  - 10.3.3.2. Market Share & Forecast
    - 10.3.3.2.1. By Component
    - 10.3.3.2.2. By Deployment
    - 10.3.3.2.3. By Enterprise Type
    - 10.3.3.2.4. By Application
    - 10.3.3.2.5. By End User

11. Market Dynamics

11.1. Drivers
11.2. Challenges

12. Market Trends & Developments

12.1. Merger & Acquisition (If Any)
12.2. Product Launches (If Any)
12.3. Recent Developments

13. Global Data Science and Predictive Analytics Market: SWOT Analysis

14. Porter's Five Forces Analysis

14.1. Competition in the Industry
14.2. Potential of New Entrants
14.3. Power of Suppliers
14.4. Power of Customers
14.5. Threat of Substitute Products

15. Competitive Landscape

15.1. Accenture plc
- 15.1.1. Business Overview
- 15.1.2. Products & Services
- 15.1.3. Recent Developments
- 15.1.4. Key Personnel
- 15.1.5. SWOT Analysis
15.2. Vention, Inc.
15.3. Absolutdata Analytics Pvt. Ltd.
15.4. Salesforce, Inc.
15.5. Manthan Software Services Pvt. Ltd.
15.6. LatentView Analytics Private Limited
15.7. Oracle Corporation
15.8. SG Analytics, Inc.
15.9. Mu Sigma Inc.
15.10. Fractal Analytics Private Limited