세계의 데이터 사이언스 플랫폼 시장 : 컴포넌트별, 조직 규모별, 비즈니스 기능별, 전개별, 업계별 예측(2025-2030년)

The Data Science Platform Market was valued at USD 76.83 billion in 2023, expected to reach USD 92.47 billion in 2024, and is projected to grow at a CAGR of 20.44%, to USD 282.59 billion by 2030.

The Data Science Platform market encompasses a broad scope defined by the growing need for advanced analytics, machine learning, and artificial intelligence tools that transform raw data into actionable insights. This platform necessitates scalable and flexible solutions to handle vast data sets, integrate diverse data sources, and provide user-friendly interfaces to facilitate data-driven decisions across industries. Its applications span various sectors, including finance, healthcare, retail, and manufacturing, where it enables predictive analytics, operational optimization, and personalized customer experiences. End-use scope includes businesses, government agencies, and academic institutions seeking to enhance decision-making processes and innovate their service offerings. Key growth factors include the increasing demand for big data analytics, cloud computing advancements, and the proliferation of IoT devices, providing potential opportunities such as developing domain-specific solutions and leveraging emerging technologies like quantum computing. Current market dynamics offer opportunities for companies to innovate solutions that enhance data security and improve automation capabilities while addressing user experience challenges. However, market growth faces limitations like high implementation costs, data privacy concerns, and a shortage of skilled professionals, which can hinder adoption. Challenging factors such as rapidly evolving technology standards and the complexity of integrating new systems with legacy infrastructures are significant hurdles. To propel business growth, research and development should focus on AI-driven analytics, real-time data processing, and enhancing data collaboration features across platforms. Innovations in self-service analytics and the democratization of data access can also be pivotal. Understanding the nature of this competitive and rapidly evolving market involves acknowledging how collaboration between data scientists, IT professionals, and business strategists is crucial to meet changing demands. Companies that can swiftly adapt to technological changes, address customer pain points, and offer tailored, robust data science solutions are well-positioned to succeed within this dynamic landscape.

Market Dynamics: Unveiling Key Market Insights in the Rapidly Evolving Data Science Platform Market

The Data Science Platform Market is undergoing transformative changes driven by a dynamic interplay of supply and demand factors. Understanding these evolving market dynamics prepares business organizations to make informed investment decisions, refine strategic decisions, and seize new opportunities. By gaining a comprehensive view of these trends, business organizations can mitigate various risks across political, geographic, technical, social, and economic domains while also gaining a clearer understanding of consumer behavior and its impact on manufacturing costs and purchasing trends.

• Market Drivers
  • Increasing focus on data-driven business decisions
  • Rising adoption rates with demand for improved marketing & sales strategies
  • Growing demand to extract meaningful insights from voluminous data
• Market Restraints
  • High cost of solution
• Market Opportunities
  • Integrated platform with advanced technology such as AI & ML enabling intelligent business solutions
  • Expanding end-use industries and increasing investment in productivity-boosting technologies
• Market Challenges
  • Data privacy and security issues

Porter's Five Forces: A Strategic Tool for Navigating the Data Science Platform Market

Porter's five forces framework is a critical tool for understanding the competitive landscape of the Data Science Platform Market. It offers business organizations with a clear methodology for evaluating their competitive positioning and exploring strategic opportunities. This framework helps businesses assess the power dynamics within the market and determine the profitability of new ventures. With these insights, business organizations can leverage their strengths, address weaknesses, and avoid potential challenges, ensuring a more resilient market positioning.

PESTLE Analysis: Navigating External Influences in the Data Science Platform Market

External macro-environmental factors play a pivotal role in shaping the performance dynamics of the Data Science Platform Market. Political, Economic, Social, Technological, Legal, and Environmental factors analysis provides the necessary information to navigate these influences. By examining PESTLE factors, businesses can better understand potential risks and opportunities. This analysis enables business organizations to anticipate changes in regulations, consumer preferences, and economic trends, ensuring they are prepared to make proactive, forward-thinking decisions.

Market Share Analysis: Understanding the Competitive Landscape in the Data Science Platform Market

A detailed market share analysis in the Data Science Platform Market provides a comprehensive assessment of vendors' performance. Companies can identify their competitive positioning by comparing key metrics, including revenue, customer base, and growth rates. This analysis highlights market concentration, fragmentation, and trends in consolidation, offering vendors the insights required to make strategic decisions that enhance their position in an increasingly competitive landscape.

FPNV Positioning Matrix: Evaluating Vendors' Performance in the Data Science Platform Market

The Forefront, Pathfinder, Niche, Vital (FPNV) Positioning Matrix is a critical tool for evaluating vendors within the Data Science Platform Market. This matrix enables business organizations to make well-informed decisions that align with their goals by assessing vendors based on their business strategy and product satisfaction. The four quadrants provide a clear and precise segmentation of vendors, helping users identify the right partners and solutions that best fit their strategic objectives.

Strategy Analysis & Recommendation: Charting a Path to Success in the Data Science Platform Market

A strategic analysis of the Data Science Platform Market is essential for businesses looking to strengthen their global market presence. By reviewing key resources, capabilities, and performance indicators, business organizations can identify growth opportunities and work toward improvement. This approach helps businesses navigate challenges in the competitive landscape and ensures they are well-positioned to capitalize on newer opportunities and drive long-term success.

Key Company Profiles

The report delves into recent significant developments in the Data Science Platform Market, highlighting leading vendors and their innovative profiles. These include Altair Engineering Inc., Alteryx, Inc., Anaconda Inc., Civis Analytics, Inc., Cloudera, Inc., Domino Data Lab, Inc., Fair Issac Corporation, Google LLC by Alphabet Inc., International Business Machines Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., Teradata Corporation, and Tibco Software Inc..

Market Segmentation & Coverage

This research report categorizes the Data Science Platform Market to forecast the revenues and analyze trends in each of the following sub-markets:

• Based on Component, market is studied across Platform and Services. The Services is further studied across Managed Services and Professional Services.
• Based on Organization Size, market is studied across Large Enterprises and Small & Medium-Sized Enterprises.
• Based on Business Function, market is studied across Customer Support, Finance & Accounting, Logistics, Marketing, and Sales.
• Based on Deployment, market is studied across On-Cloud and On-Premises.
• Based on Industry Vertical, market is studied across Banking, Financial Services, & Insurance, Energy & Utilities, Government & Defense, Healthcare & Life Sciences, Manufacturing, Media & Entertainment, Retail & Ecommerce, Telecom & IT, and Transportation & Logistics.
• Based on Region, market is studied across Americas, Asia-Pacific, and Europe, Middle East & Africa. The Americas is further studied across Argentina, Brazil, Canada, Mexico, and United States. The United States is further studied across California, Florida, Illinois, New York, Ohio, Pennsylvania, and Texas. The Asia-Pacific is further studied across Australia, China, India, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand, and Vietnam. The Europe, Middle East & Africa is further studied across Denmark, Egypt, Finland, France, Germany, Israel, Italy, Netherlands, Nigeria, Norway, Poland, Qatar, Russia, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, and United Kingdom.

The report offers a comprehensive analysis of the market, covering key focus areas:

1. Market Penetration: A detailed review of the current market environment, including extensive data from top industry players, evaluating their market reach and overall influence.

2. Market Development: Identifies growth opportunities in emerging markets and assesses expansion potential in established sectors, providing a strategic roadmap for future growth.

3. Market Diversification: Analyzes recent product launches, untapped geographic regions, major industry advancements, and strategic investments reshaping the market.

4. Competitive Assessment & Intelligence: Provides a thorough analysis of the competitive landscape, examining market share, business strategies, product portfolios, certifications, regulatory approvals, patent trends, and technological advancements of key players.

5. Product Development & Innovation: Highlights cutting-edge technologies, R&D activities, and product innovations expected to drive future market growth.

The report also answers critical questions to aid stakeholders in making informed decisions:

1. What is the current market size, and what is the forecasted growth?

2. Which products, segments, and regions offer the best investment opportunities?

3. What are the key technology trends and regulatory influences shaping the market?

4. How do leading vendors rank in terms of market share and competitive positioning?

5. What revenue sources and strategic opportunities drive vendors' market entry or exit strategies?

Table of Contents

1. Preface

• 1.1. Objectives of the Study
• 1.2. Market Segmentation & Coverage
• 1.3. Years Considered for the Study
• 1.4. Currency & Pricing
• 1.5. Language
• 1.6. Stakeholders

2. Research Methodology

• 2.1. Define: Research Objective
• 2.2. Determine: Research Design
• 2.3. Prepare: Research Instrument
• 2.4. Collect: Data Source
• 2.5. Analyze: Data Interpretation
• 2.6. Formulate: Data Verification
• 2.7. Publish: Research Report
• 2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

• 5.1. Market Dynamics
  • 5.1.1. Drivers
    • 5.1.1.1. Increasing focus on data-driven business decisions
    • 5.1.1.2. Rising adoption rates with demand for improved marketing & sales strategies
    • 5.1.1.3. Growing demand to extract meaningful insights from voluminous data
  • 5.1.2. Restraints
    • 5.1.2.1. High cost of solution
  • 5.1.3. Opportunities
    • 5.1.3.1. Integrated platform with advanced technology such as AI & ML enabling intelligent business solutions
    • 5.1.3.2. Expanding end-use industries and increasing investment in productivity-boosting technologies
  • 5.1.4. Challenges
    • 5.1.4.1. Data privacy and security issues
• 5.2. Market Segmentation Analysis
• 5.3. Porter's Five Forces Analysis
  • 5.3.1. Threat of New Entrants
  • 5.3.2. Threat of Substitutes
  • 5.3.3. Bargaining Power of Customers
  • 5.3.4. Bargaining Power of Suppliers
  • 5.3.5. Industry Rivalry
• 5.4. PESTLE Analysis
  • 5.4.1. Political
  • 5.4.2. Economic
  • 5.4.3. Social
  • 5.4.4. Technological
  • 5.4.5. Legal
  • 5.4.6. Environmental

6. Data Science Platform Market, by Component

• 6.1. Introduction
• 6.2. Platform
• 6.3. Services
  • 6.3.1. Managed Services
  • 6.3.2. Professional Services

7. Data Science Platform Market, by Organization Size

• 7.1. Introduction
• 7.2. Large Enterprises
• 7.3. Small & Medium-Sized Enterprises

8. Data Science Platform Market, by Business Function

• 8.1. Introduction
• 8.2. Customer Support
• 8.3. Finance & Accounting
• 8.4. Logistics
• 8.5. Marketing
• 8.6. Sales

9. Data Science Platform Market, by Deployment

• 9.1. Introduction
• 9.2. On-Cloud
• 9.3. On-Premises

10. Data Science Platform Market, by Industry Vertical

• 10.1. Introduction
• 10.2. Banking, Financial Services, & Insurance
• 10.3. Energy & Utilities
• 10.4. Government & Defense
• 10.5. Healthcare & Life Sciences
• 10.6. Manufacturing
• 10.7. Media & Entertainment
• 10.8. Retail & Ecommerce
• 10.9. Telecom & IT
• 10.10. Transportation & Logistics

11. Americas Data Science Platform Market

• 11.1. Introduction
• 11.2. Argentina
• 11.3. Brazil
• 11.4. Canada
• 11.5. Mexico
• 11.6. United States

12. Asia-Pacific Data Science Platform Market

• 12.1. Introduction
• 12.2. Australia
• 12.3. China
• 12.4. India
• 12.5. Indonesia
• 12.6. Japan
• 12.7. Malaysia
• 12.8. Philippines
• 12.9. Singapore
• 12.10. South Korea
• 12.11. Taiwan
• 12.12. Thailand
• 12.13. Vietnam

13. Europe, Middle East & Africa Data Science Platform Market

• 13.1. Introduction
• 13.2. Denmark
• 13.3. Egypt
• 13.4. Finland
• 13.5. France
• 13.6. Germany
• 13.7. Israel
• 13.8. Italy
• 13.9. Netherlands
• 13.10. Nigeria
• 13.11. Norway
• 13.12. Poland
• 13.13. Qatar
• 13.14. Russia
• 13.15. Saudi Arabia
• 13.16. South Africa
• 13.17. Spain
• 13.18. Sweden
• 13.19. Switzerland
• 13.20. Turkey
• 13.21. United Arab Emirates
• 13.22. United Kingdom

14. Competitive Landscape

• 14.1. Market Share Analysis, 2023
• 14.2. FPNV Positioning Matrix, 2023
• 14.3. Competitive Scenario Analysis
• 14.4. Strategy Analysis & Recommendation

Companies Mentioned

• 1. Altair Engineering Inc.
• 2. Alteryx, Inc.
• 3. Anaconda Inc.
• 4. Civis Analytics, Inc.
• 5. Cloudera, Inc.
• 6. Domino Data Lab, Inc.
• 7. Fair Issac Corporation
• 8. Google LLC by Alphabet Inc.
• 9. International Business Machines Corporation
• 10. Microsoft Corporation
• 11. Oracle Corporation
• 12. SAP SE
• 13. SAS Institute Inc.
• 14. Teradata Corporation
• 15. Tibco Software Inc.