日本のデータサイエンスプラットフォーム市場レポート：コンポーネント、用途、業界、地域別、2025年～2033年

日本のデータサイエンスプラットフォーム市場の市場規模は2024年に43億米ドルに達しました。今後、IMARC Groupは、同市場が2033年までに142億米ドルに達し、2025年から2033年にかけて14.2%の成長率（CAGR）を示すと予測しています。ヘルスケア分野におけるデータサイエンスプラットフォームの採用の増加、多様なビジネスにおけるクラウドベースのソリューションに対するニーズの高まり、データサイエンスプラットフォームへの先端技術の注入の増加は、市場成長を促進する主な要因の1つです。

本レポートで扱う主な質問

• 日本のデータサイエンスプラットフォーム市場はこれまでどのように推移してきたか、また今後どのように推移していくか？
• COVID-19の日本のデータサイエンスプラットフォーム市場への影響は？
• 日本のデータサイエンスプラットフォーム市場のコンポーネント別の内訳は？
• 日本のデータサイエンスプラットフォーム市場の用途別の内訳は？
• 日本のデータサイエンスプラットフォーム市場の業界別の内訳は？
• 日本のデータサイエンスプラットフォーム市場のバリューチェーンにはどのような段階がありますか？
• 日本のデータサイエンスプラットフォームにおける主な促進要因と課題は何か？
• 日本のデータサイエンスプラットフォーム市場の構造と主要プレーヤーは？
• 日本のデータサイエンスプラットフォーム市場における競合の程度は？

目次

第1章 序文

第2章 調査範囲と調査手法

• 調査の目的
• ステークホルダー
• データソース
• 市場推定
• 調査手法

第3章 エグゼクティブサマリー

第4章 日本のデータサイエンスプラットフォーム市場：イントロダクション

• 概要
• 市場力学
• 業界動向
• 競合情報

第5章 日本のデータサイエンスプラットフォーム市場情勢

• 過去および現在の市場動向（2019年～2024年）
• 市場予測（2025-2033）

第6章 日本のデータサイエンスプラットフォーム市場：コンポーネント別の内訳

• ソフトウェア
• サービス

第7章 日本のデータサイエンスプラットフォーム市場：用途別の内訳

• マーケティングとセールス
• ロジスティクス
• 財務と会計
• カスタマーサポート
• その他

第8章 日本のデータサイエンスプラットフォーム市場：業界別の内訳

• IT・通信
• ヘルスケア
• BFSI
• 製造
• 小売業とeコマース
• その他

第9章 日本のデータサイエンスプラットフォーム市場：競合情勢

• 概要
• 市場構造
• 市場プレーヤーのポジショニング
• 主要成功戦略
• 競合ダッシュボード
• 企業評価象限

第10章 主要企業のプロファイル

第11章 日本のデータサイエンスプラットフォーム市場：業界分析

• 促進要因・抑制要因・機会
• ポーターのファイブフォース分析
• バリューチェーン分析

第12章 付録

Japan data science platform market size reached USD 4.3 Billion in 2024. Looking forward, IMARC Group expects the market to reach USD 14.2 Billion by 2033, exhibiting a growth rate (CAGR) of 14.2% during 2025-2033. Increased adoption of data science platforms within the healthcare sector, the escalating need for cloud-based solutions across diverse businesses, and the growing infusion of advanced technologies into data science platforms are among the primary factors propelling market growth.

A data science platform comprises an extensive infrastructure encompassing software and hardware components, offering the essential tools, technologies, and resources to facilitate various stages of the data science workflow. Data science is a multifaceted discipline that encompasses tasks such as data collection, data cleansing, data analysis, and data interpretation, all aimed at extracting valuable insights and supporting data-driven decision-making. These platforms provide an array of capabilities, including tools for data extraction, transformation, and loading (ETL), along with connectors enabling access to diverse data sources such as databases, data warehouses, APIs, and more. Moreover, they furnish a wide spectrum of machine learning algorithms and modeling tools for constructing predictive and descriptive models.

Japan Data Science Platform Market Trends:

Presently, the growth of the data science platform market in Japan is primarily steered by the escalating adoption within the healthcare sector, where these platforms efficiently manage, analyze, and integrate substantial volumes of both structured and unstructured data. Additionally, there is an increasing preference for cloud-based solutions across diverse global business entities, contributing to a favorable market environment. Furthermore, there is a rising demand for cost-effective and efficient decision-making tools on a wide scale. This growing demand, combined with the expanding use of data science platforms that enhance enterprise analysis and productivity, is driving market expansion. Moreover, the incorporation of artificial intelligence (AI), the Internet of Things (IoT), and machine learning (ML) into data science platforms is creating promising growth prospects for industry participants. Besides this, the increasing need for data science platforms, which offer a unified and integrated approach to constructing, managing, and optimizing predictive models for businesses, is positively impacting the market. Furthermore, the surging demand for data science platforms due to the evolution of big data technologies is contributing to market growth. Moreover, the heightened requirement for data science platforms within the BFSI sector, driven by the increased use of banking services, is expected to reinforce market expansion in Japan over the forecasted period.

Japan Data Science Platform Market Segmentation:

Component Insights:

• Software
• Services

Application Insights:

• Marketing and Sales
• Logistics
• Finance and Accounting
• Customer Support
• Others

Vertical Insights:

• IT and Telecommunication
• Healthcare
• BFSI
• Manufacturing
• Retail and E-Commerce
• Others

Competitive Landscape:

The market research report has also provided a comprehensive analysis of the competitive landscape. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

Key Questions Answered in This Report:

• How has the Japan data science platform market performed so far and how will it perform in the coming years?
• What has been the impact of COVID-19 on the Japan data science platform market?
• What is the breakup of the Japan data science platform market on the basis of component?
• What is the breakup of the Japan data science platform market on the basis of application?
• What is the breakup of the Japan data science platform market on the basis of vertical?
• What are the various stages in the value chain of the Japan data science platform market?
• What are the key driving factors and challenges in the Japan data science platform?
• What is the structure of the Japan data science platform market and who are the key players?
• What is the degree of competition in the Japan data science platform market?

Table of Contents

1 Preface

2 Scope and Methodology

• 2.1 Objectives of the Study
• 2.2 Stakeholders
• 2.3 Data Sources
  • 2.3.1 Primary Sources
  • 2.3.2 Secondary Sources
• 2.4 Market Estimation
  • 2.4.1 Bottom-Up Approach
  • 2.4.2 Top-Down Approach
• 2.5 Forecasting Methodology

3 Executive Summary

4 Japan Data Science Platform Market - Introduction

• 4.1 Overview
• 4.2 Market Dynamics
• 4.3 Industry Trends
• 4.4 Competitive Intelligence

5 Japan Data Science Platform Market Landscape

• 5.1 Historical and Current Market Trends (2019-2024)
• 5.2 Market Forecast (2025-2033)

6 Japan Data Science Platform Market - Breakup by Component

• 6.1 Software
  • 6.1.1 Overview
  • 6.1.2 Historical and Current Market Trends (2019-2024)
  • 6.1.3 Market Forecast (2025-2033)
• 6.2 Services
  • 6.2.1 Overview
  • 6.2.2 Historical and Current Market Trends (2019-2024)
  • 6.2.3 Market Forecast (2025-2033)

7 Japan Data Science Platform Market - Breakup by Application

• 7.1 Marketing and Sales
  • 7.1.1 Overview
  • 7.1.2 Historical and Current Market Trends (2019-2024)
  • 7.1.3 Market Forecast (2025-2033)
• 7.2 Logistics
  • 7.2.1 Overview
  • 7.2.2 Historical and Current Market Trends (2019-2024)
  • 7.2.3 Market Forecast (2025-2033)
• 7.3 Finance and Accounting
  • 7.3.1 Overview
  • 7.3.2 Historical and Current Market Trends (2019-2024)
  • 7.3.3 Market Forecast (2025-2033)
• 7.4 Customer Support
  • 7.4.1 Overview
  • 7.4.2 Historical and Current Market Trends (2019-2024)
  • 7.4.3 Market Forecast (2025-2033)
• 7.5 Others
  • 7.5.1 Historical and Current Market Trends (2019-2024)
  • 7.5.2 Market Forecast (2025-2033)

8 Japan Data Science Platform Market - Breakup by Vertical

• 8.1 IT and Telecommunication
  • 8.1.1 Overview
  • 8.1.2 Historical and Current Market Trends (2019-2024)
  • 8.1.3 Market Forecast (2025-2033)
• 8.2 Healthcare
  • 8.2.1 Overview
  • 8.2.2 Historical and Current Market Trends (2019-2024)
  • 8.2.3 Market Forecast (2025-2033)
• 8.3 BFSI
  • 8.3.1 Overview
  • 8.3.2 Historical and Current Market Trends (2019-2024)
  • 8.3.3 Market Forecast (2025-2033)
• 8.4 Manufacturing
  • 8.4.1 Overview
  • 8.4.2 Historical and Current Market Trends (2019-2024)
  • 8.4.3 Market Forecast (2025-2033)
• 8.5 Retail and E-Commerce
  • 8.5.1 Overview
  • 8.5.2 Historical and Current Market Trends (2019-2024)
  • 8.5.3 Market Forecast (2025-2033)
• 8.6 Others
  • 8.6.1 Historical and Current Market Trends (2019-2024)
  • 8.6.2 Market Forecast (2025-2033)

9 Japan Data Science Platform Market - Competitive Landscape

• 9.1 Overview
• 9.2 Market Structure
• 9.3 Market Player Positioning
• 9.4 Top Winning Strategies
• 9.5 Competitive Dashboard
• 9.6 Company Evaluation Quadrant

10 Profiles of Key Players

• 10.1 Company A
  • 10.1.1 Business Overview
  • 10.1.2 Product Portfolio
  • 10.1.3 Business Strategies
  • 10.1.4 SWOT Analysis
  • 10.1.5 Major News and Events
• 10.2 Company B
  • 10.2.1 Business Overview
  • 10.2.2 Product Portfolio
  • 10.2.3 Business Strategies
  • 10.2.4 SWOT Analysis
  • 10.2.5 Major News and Events
• 10.3 Company C
  • 10.3.1 Business Overview
  • 10.3.2 Product Portfolio
  • 10.3.3 Business Strategies
  • 10.3.4 SWOT Analysis
  • 10.3.5 Major News and Events
• 10.4 Company D
  • 10.4.1 Business Overview
  • 10.4.2 Product Portfolio
  • 10.4.3 Business Strategies
  • 10.4.4 SWOT Analysis
  • 10.4.5 Major News and Events
• 10.5 Company E
  • 10.5.1 Business Overview
  • 10.5.2 Product Portfolio
  • 10.5.3 Business Strategies
  • 10.5.4 SWOT Analysis
  • 10.5.5 Major News and Events

11 Japan Data Science Platform Market - Industry Analysis

• 11.1 Drivers, Restraints, and Opportunities
  • 11.1.1 Overview
  • 11.1.2 Drivers
  • 11.1.3 Restraints
  • 11.1.4 Opportunities
• 11.2 Porters Five Forces Analysis
  • 11.2.1 Overview
  • 11.2.2 Bargaining Power of Buyers
  • 11.2.3 Bargaining Power of Suppliers
  • 11.2.4 Degree of Competition
  • 11.2.5 Threat of New Entrants
  • 11.2.6 Threat of Substitutes
• 11.3 Value Chain Analysis

12 Appendix