资料科学与预测分析市场－全球产业规模、份额、趋势、机会及预测（按组件、部署类型、企业类型、应用、最终用户、地区和竞争格局划分，2021-2031年）

全球资料科学与预测分析市场预计将从2025年的195.4亿美元成长到2031年的713.4亿美元，复合年增长率（CAGR）为24.09%。该市场涵盖了利用先进的软体平台和调查方法从复杂资料集中提取可操作的洞察并预测未来结果的领域。推动市场成长的关键因素包括企业资料量的指数级成长以及即时商业商业智慧在优化营运效率方面日益增长的重要性。同时，可扩展云端基础设施的日益普及也降低了高效能分析工具的使用门槛，进一步推动了这些因素的发展。

然而，该行业面临一项重大挑战：开发和管理这些先进系统所需的技能人才严重短缺。根据电脑产业协会（CompTIA）预测，到2024年，未来十年对资料科学家和分析师的就业需求预计将成长约35%，这一成长远超整体劳动市场。这种持续存在的技能缺口限制了预测模型的有效应用，并造成了瓶颈，阻碍了全球市场扩张的潜在速度。

市场驱动因素

人工智慧 (AI) 和机器学习技术的深度融合正在从根本上改变分析平台的功能，使其重心从历史报告转向前瞻性洞察。现代演算法能够自动执行复杂的资料处理任务，使企业能够以前所未有的速度和精度摄取非结构化资料集并产生预测模型。对于希望在其分析工作流程中应用生成模型的企业而言，这种技术整合至关重要。 IBM 于 2024 年 1 月发布的《2023 年全球 AI 采用指数》也印证了这一趋势，该指数指出，42% 的企业级组织正在积极地在其业务中采用 AI。这推动了对能够管理这些智慧工作流程的高阶资料科学工具的需求。

同时，云端分析基础架构的广泛应用为处理此类精准预测所需的大型资料集奠定了至关重要的基础。云端环境提供了运行资源彙整密集型演算法所需的弹性扩展性和运算能力，无需对本地硬体进行巨额资本投入，从而促进了即时协作，并使高效能运算资源的获取更加普及。根据 Flexera 于 2024 年 3 月发布的《2024 年云端状态报告》，51% 的组织表示大量使用公共云端，而微软承诺在 2024 年投资 33 亿欧元用于扩展其在德国的人工智慧和云端中心容量，也印证了这一强劲的发展势头。

市场挑战

熟练的专业人才短缺是全球资料科学和预测分析市场成长的一大障碍。儘管企业拥有大量资料和先进的分析平台，但缺乏能够解读复杂资料集的合格人员阻碍了这些技术的成功应用。人才短缺导致计划延期、营运成本增加，以及分析专案投资回报率（ROI）无法充分实现，迫使许多公司缩减数位化倡议规模，并减缓了预测软体的普及速度。

近期有关劳动力准备的产业数据也印证了这一瓶颈：世界经济论坛指出，63%的雇主认为技能缺口是2025年企业转型面临的主要障碍。这种技术能力的不足阻碍了企业将预测模型有效整合到核心营运中，造成了人力资本供应落后于技术能力的结构性限制，限制了该产业在全球快速扩张的潜力。

市场趋势

透过 MLOps 和 DataOps 实践实现模型运行化，正在重塑市场格局，并为预测演算法的生命週期管理建立标准化框架。随着企业从实验性试点阶段过渡到实际应用，重点正转向建立稳健的工程流程，以确保模型在生产环境中的可重复性、持续监控和自动重新训练，从而解决以往成功原型因资料漂移而无法扩展或效能下降的问题。这一趋势的加速发展在近期的采用指标中显而易见。根据 Databricks 于 2024 年 6 月发布的《2024 年资料与人工智慧现况报告》，企业运作的机器学习模型数量年增 411%，这标誌着企业正从专案分析转向整合化的、创造价值的维运工作流程。

同时，在动态商业环境中对即时响应的需求驱动下，市场正转向即时和串流数据分析。传统的批次方式按设定的时间间隔分析历史数据，而事件驱动架构则与之互补，后者能够即时处理生成的信息，使预测系统能够摄取高速数据，从而实现即时决策。技术决策者日益认识到这项能力的战略重要性。根据 Confluent 于 2024 年 6 月发布的《2024 年资料流报告》，86% 的 IT 领导者将资料流列为 2024 年 IT 投资的首要或关键策略重点，这证实了企业正在优先考虑利用「动态资料」来获得竞争优势的能力。

目录

第一章概述

第二章调查方法

第三章执行摘要

第四章：客户评价

第五章：全球资料科学与预测分析市场展望

• 市场规模及预测
  • 按金额
• 市占率及预测
  • 按组件（解决方案、服务）
  • 依部署类型（云端、本机部署）
  • 按公司规模（大型公司、中小企业）
  • 按应用领域（财务风险分析、行销/销售分析、客户分析、供应链分析）
  • 按最终用户划分（银行、金融和保险、汽车、IT和通讯、医疗保健、零售、能源和公共产业、政府等）
  • 按地区
  • 按公司（2025 年）
• 市场地图

6. 北美资料科学与预测分析市场展望

• 市场规模及预测
• 市占率及预测
• 北美洲：国家分析
  • 美国
  • 加拿大
  • 墨西哥

7. 欧洲资料科学与预测分析市场展望

• 市场规模及预测
• 市占率及预测
• 欧洲：国家分析
  • 德国
  • 法国
  • 英国
  • 义大利
  • 西班牙

8. 亚太地区资料科学与预测分析市场展望

• 市场规模及预测
• 市占率及预测
• 亚太地区：国家分析
  • 中国
  • 印度
  • 日本
  • 韩国
  • 澳洲

9. 中东和非洲资料科学与预测分析市场展望

• 市场规模及预测
• 市占率及预测
• 中东和非洲：国家分析
  • 沙乌地阿拉伯
  • 阿拉伯聯合大公国
  • 南非

10. 南美洲资料科学与预测分析市场展望

• 市场规模及预测
• 市占率及预测
• 南美洲：国家分析
  • 巴西
  • 哥伦比亚
  • 阿根廷

第十一章 市场动态

• 司机
• 任务

第十二章 市场趋势与发展

• 併购
• 产品发布
• 最新进展

第十三章 全球资料科学与预测分析市场：SWOT分析

第十四章：波特五力分析

• 产业竞争
• 新进入者的可能性
• 供应商电力
• 顾客权力
• 替代品的威胁

第十五章 竞争格局

• 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

第十六章 策略建议

第十七章：关于研究公司及免责声明

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.

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:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

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

16. Strategic Recommendations

17. About Us & Disclaimer