自律型データプラットフォームの世界市場規模：コンポーネント別、業界別、地域範囲別および予測

自律型データプラットフォームの市場規模と予測

自律型データプラットフォーム市場規模は、2024年に19億5,000万米ドルと評価され、2026～2032年にかけて22.10％のCAGRで成長し、2032年には96億3,000万米ドルに達すると予測されます。

技術的進歩によるクラウドベースのソリューション採用の増加、コグニティブコンピューティング技術と先進的分析の採用の高まりが、予測される年数にわたって自律型データプラットフォーム市場を牽引すると期待されます。当レポートでは、自律型データプラットフォームの世界市場について包括的な評価を行います。主要セグメント、動向、市場促進要因、競合情勢、市場で重要な役割を果たしている要因などを包括的に分析しています。

世界の自律型データプラットフォーム市場の定義

自律型データツールは、特定の顧客のビッグデータインフラを分析し、企業の重要な問題に対処し、最適なデータベース利用を確保します。これは、人工知能（AI）や機械学習（ML）などの様々なコグニティブコンピューティングプラットフォームを活用することで、それ自体を管理・最適化するデータ分析プラットフォームです。

ヒューリスティックと機械学習の組み合わせを活用することで、洞察、実用的なアラート、推奨事項をユーザーに提供し、その結果、高いパフォーマンス、ワークロードの継続性、コスト削減を実現します。運用効率を高め、プロセスを容易にします。コンポーネントに基づき、市場はサポート＆メンテナンス、サービス、プラットフォーム、統合、アドバイザリーに分類されます。業種別では、通信メディア、小売、製造、ヘルスケア・ライフサイエンス、その他に分類されます。

自律型データプラットフォームの世界市場概要

技術の進歩によるクラウドベースのソリューションの採用の増加、コグニティブコンピューティング技術と先進的分析の採用の増加が、予測される年数にわたって自律型データプラットフォーム市場を牽引すると期待されます。また、ソーシャルメディアや相互接続されたデバイスの利用増加に伴う非構造化データ量の増加が、今後数年間で市場を押し上げると予想されます。

さらに、拡大可能で非構造化かつ複雑なデータの導入や、小売業者によるオムニチャネル体験に対する需要の増加は、予測期間中に市場を活性化させると予想されます。市場成長を阻害する要因や課題も存在します。熟練した専門家の不足や複雑な分析プロセスなどの要因が市場抑制要因として作用する可能性が高いです。

目次

第1章 自律型データプラットフォームの世界市場導入

• 市場概要
• 調査範囲
• 前提条件

第2章 エグゼクティブサマリー

第3章 VERIFIED MARKET RESEARCHの調査手法

• データマイニング
• バリデーション
• 一次資料
• データソース一覧

第4章 自律型データプラットフォームの世界市場展望

• 概要
• 市場力学
  • 促進要因
  • 抑制要因
  • 機会
• ポーターのファイブフォースモデル
• バリューチェーン分析

第5章 自律型データプラットフォームの世界市場：コンポーネント別

• 概要
• サポートとメンテナンス
• サービス
• プラットフォーム
• インテグレーション
• アドバイザリー

第6章 自律型データプラットフォームの世界市場：業界別

• 概要
• 通信メディア
• 小売
• BFSI
• 製造業
• ヘルスケア・ライフサイエンス
• その他

第7章 自律型データプラットフォームの世界市場、地域別

• 概要
• 北米
  • 米国
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • 英国
  • フランス
  • その他の欧州
• アジア太平洋
  • 中国
  • 日本
  • インド
  • その他のアジア太平洋
• その他
  • ラテンアメリカ
  • 中東・アフリカ

第8章 世界の自律型データプラットフォーム市場の競合情勢

• 概要
• 各社の市場ランキング
• 主要開発戦略

第9章 企業プロファイル

• Oracle Corporation
• Teradata Corporation
• IBM Corporation
• Amazon Web Services, Inc.
• MapR
• Cloudera, Inc.
• Qubole, Inc.
• Ataccama Corporation
• Gemini Data, Inc.
• DvSum

第10章 主要開発

• 製品上市/開発
• 合併と買収
• 事業拡大
• パートナーシップと提携

第11章 付録

• 関連調査

Autonomous Data Platform Market Size And Forecast

Autonomous Data Platform Market size was valued at USD 1.95 Billion in 2024 and is projected to reach USD 9.63 Billion by 2032, growing at a CAGR of 22.10 % from 2026 to 2032.

The increasing adoption of cloud-based solutions owing to technological advancement and the rising adoption of cognitive computing technology & advanced analytics are expected to drive the Autonomous Data Platform Market over the predicted years. The Global Autonomous Data Platform Market report provides a holistic evaluation of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, competitive landscape, and factors that are playing a substantial role in the market.

Global Autonomous Data Platform Market Definition

The autonomous data tool analyses a specific customer's big data infrastructure to address crucial company problems and ensure optimal database usage. It is a data and analytics platform that manages and optimizes itself by leveraging various cognitive computing platforms, such as Artificial Intelligence (AI), and Machine Learning (ML).

By making use of the combination of heuristics and machine learning, it serves insights, actionable alerts, and recommendations to the users, which results in ensuring high performance, workload continuity, and cost savings. It enhances operational efficiency and makes the process easier. Based on the component, the market is classified into Support & Maintenance, Services, Platform, Integration, and Advisory. Based on the vertical, the market is bifurcated into Telecommunication & Media, Retail, Manufacturing, Healthcare & Life Sciences, and Others.

Global Autonomous Data Platform Market Overview

The increasing adoption of cloud-based solutions owing to the advancement in technologies and the rising adoption of cognitive computing technology & advanced analytics are expected to drive the Autonomous Data Platform Market over the predicted years. Also, the growing volume of unstructured data with respect to the increasing utilization of social media & interconnected devices expects a boost to the market in the coming years.

Moreover, the introduction of expandable, unstructured, & complex data and the increasing demand for omnichannel experience from retailers are anticipated to fuel the market during the forecasted period. There are certain restraints and challenges faced which can hinder market growth. Factors such as the dearth of skilled professionals and complicated analytical processes are likely to act as market restraints.

Global Autonomous Data Platform Market: Segmentation Analysis

The Global Autonomous Data Platform Market is Segmented on the basis of Component, Vertical, And Geography.

Autonomous Data Platform Market, By Component

• Support and Maintenance
• Services
• Platform
• Integration
• Advisory

Based on Component, the market is bifurcated into Support & Maintenance, Services, Platform, Integration, and Advisory. A wide range of applications of the Autonomous Data Platform in various industry segments is expected to bolster the market demand in the coming years.

Autonomous Data Platform Market, By Vertical

• Telecommunication & Media
• Retail
• BFSI
• Manufacturing
• Healthcare and Life Sciences
• Others

Based on Vertical, the market is bifurcated into Telecommunication & Media, Retail, BFSI, Manufacturing, Healthcare & Life Sciences, and Others. BFSI segment is predicted to hold the most significant CAGR in the forecasted period due to the rapid adoption of the Autonomous Data Platform in this segment.

Autonomous Data Platform Market, By Geography

• North America
• Europe
• Asia Pacific
• Rest of the world
• On the basis of Regional Analysis, the Global Autonomous Data Platform Market is classified into North America, Europe, Asia Pacific, and the Rest of the world. The largest share in the market will be dominated by Europe owing to the rise of inconsistent data generated across organizations in different European countries.

Key Players

The "Global Autonomous Data Platform Market" study report will provide valuable insight with an emphasis on the global market including some of the major players such as Oracle Corporation, Teradata Corporation, IBM Corporation, Amazon Web Services, Inc., MapR, Cloudera, Inc., Qubole, Inc, Ataccama Corporation, Gemini Data, Inc, DvSum.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with its product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Key Developments

• Partnerships, Collaborations, and Agreements
• Qubole, Inc. teamed up with Ascend.io, a data engineering firm, in 2020 to combine the world's most powerful data pipeline autonomous technology with the most comprehensive data lake platform. It enables data teams to construct self-service data pipelines 7x faster and with 95% less code, lowering infrastructure costs by 50% or more while improving data processing efficiency.
• June 2020 - Anaconda, Inc., the leading Python data science platform provider, and IBM Watson have announced a new partnership to enable enterprises to adopt AI open-source technology more easily. By collaborating, the two companies hope to boost innovation and overcome the AI and data science skills gap that many businesses are experiencing. The Anaconda Team Edition repository will be integrated with IBM Watson Studio on IBM Cloud Pak for Data, allowing businesses to better manage and accelerate the adoption of AI open-source technologies across any cloud.
• Product Launches and Product Expansions
• Qubole introduced a self-service platform in June 2019 for data scientists and engineers to construct AI, machine learning, and analytics processes on their preferred public cloud.
• MapR announced new MapR Data Platform innovations in April 2019, including new, deep integrations with Kubernetes key components for primary workloads on Spark and Drill. The platform was able to better manage extremely elastic workloads as a result of this innovation.
• Oracle launched a cloud-based data science platform in 2020, with Oracle Cloud Infrastructure Data Science at its heart. It allows users to train, manage, and create machine learning algorithms on the Oracle Cloud.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL AUTONOMOUS DATA PLATFORM MARKET

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL AUTONOMOUS DATA PLATFORM MARKET OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL AUTONOMOUS DATA PLATFORM MARKET, BY COMPONENT

• 5.1 Overview
• 5.2 Support and Maintenance
• 5.3 Services
• 5.4 Platform
• 5.5 Integration
• 5.6 Advisory

6 GLOBAL AUTONOMOUS DATA PLATFORM MARKET, BY VERTICAL

• 6.1 Overview
• 6.2 Telecommunication & Media
• 6.3 Retail
• 6.4 BFSI
• 6.5 Manufacturing
• 6.6 Healthcare and Life Sciences
• 6.7 Others

7 GLOBAL AUTONOMOUS DATA PLATFORM MARKET, BY GEOGRAPHY

• 7.1 Overview
• 7.2 North America
  • 7.2.1 U.S.
  • 7.2.2 Canada
  • 7.2.3 Mexico
• 7.3 Europe
  • 7.3.1 Germany
  • 7.3.2 U.K.
  • 7.3.3 France
  • 7.3.4 Rest of Europe
• 7.4 Asia Pacific
  • 7.4.1 China
  • 7.4.2 Japan
  • 7.4.3 India
  • 7.4.4 Rest of Asia Pacific
• 7.5 Rest of the World
  • 7.5.1 Latin America
  • 7.5.2 Middle East & Africa

8 GLOBAL AUTONOMOUS DATA PLATFORM MARKET COMPETITIVE LANDSCAPE

• 8.1 Overview
• 8.2 Company Market Ranking
• 8.3 Key Development Strategies

9 COMPANY PROFILES

• 9.1 Oracle Corporation
  • 9.1.1 Overview
  • 9.1.2 Financial Performance
  • 9.1.3 Product Outlook
  • 9.1.4 Key Developments
• 9.2 Teradata Corporation
  • 9.2.1 Overview
  • 9.2.2 Financial Performance
  • 9.2.3 Product Outlook
  • 9.2.4 Key Developments
• 9.3 IBM Corporation
  • 9.3.1 Overview
  • 9.3.2 Financial Performance
  • 9.3.3 Product Outlook
  • 9.3.4 Key Developments
• 9.4 Amazon Web Services, Inc.
  • 9.4.1 Overview
  • 9.4.2 Financial Performance
  • 9.4.3 Product Outlook
  • 9.4.4 Key Developments
• 9.5 MapR
  • 9.5.1 Overview
  • 9.5.2 Financial Performance
  • 9.5.3 Product Outlook
  • 9.5.4 Key Developments
• 9.6 Cloudera, Inc.
  • 9.6.1 Overview
  • 9.6.2 Financial Performance
  • 9.6.3 Product Outlook
  • 9.6.4 Key Developments
• 9.7 Qubole, Inc.
  • 9.7.1 Overview
  • 9.7.2 Financial Performance
  • 9.7.3 Product Outlook
  • 9.7.4 Key Developments
• 9.8 Ataccama Corporation
  • 9.8.1 Overview
  • 9.8.2 Financial Performance
  • 9.8.3 Product Outlook
  • 9.8.4 Key Developments
• 9.9 Gemini Data, Inc.
  • 9.9.1 Overview
  • 9.9.2 Financial Performance
  • 9.9.3 Product Outlook
  • 9.9.4 Key Developments
• 9.10 DvSum
  • 9.10.1 Overview
  • 9.10.2 Financial Performance
  • 9.10.3 Product Outlook
  • 9.10.4 Key Developments

10 KEY DEVELOPMENTS

• 10.1 Product Launches/Developments
• 10.2 Mergers and Acquisitions
• 10.3 Business Expansions
• 10.4 Partnerships and Collaborations

11 Appendix

• 11.1 Related Research