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市場調查報告書
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1639494

巨量資料技術：市場佔有率分析、產業趨勢與統計、成長預測（2025-2030 年）

Big Data Technology - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

巨量資料技術市場規模在2025年預估為2,342.7億美元，預估至2030年將達3,757.6億美元，預測期間（2025-2030年）的複合年成長率為9.91%。

巨量資料技術-市場-IMG1

主要亮點

  • 巨量資料技術被定義為一種軟體公共事業。該技術主要用於分析、處理和提取大型資料和大量高度複雜的結構中的資訊。
  • 隨著新技術、新設備和通訊的進步，每年產生的資料量都在迅速成長。巨量資料技術和服務市場主要受評估不斷增加的結構化和非結構化資料的需求驅動，以便獲得可用於未來決策流程的可行見解。
  • 隨著工業IoT和 M2M 連接的興起，汽車產業正在為工業 4.0 做好準備。機器人、感測器、條碼閱讀器和 RFID 如今在該領域的工廠車間已很常見。由於這些小工具的存在，資料產生點激增。
  • 供需因素在消費性電子業務中發揮關鍵作用。該產業部門從巨量資料分析中受益匪淺，使其能夠從推動式市場策略轉變為拉動式市場策略。
  • 此外，產生和儲存的大量資料很容易受到相關人員和相關人員的駭客攻擊和篡改。這使得儲存資料的安全性面臨風險。巨量資料技術供應商將立即感受到影響，其聲譽也將面臨風險。

巨量資料技術市場趨勢

零售業佔據市場主導地位

  • 巨量資料技術和進階分析正在變革時期零售業。隨著電子商務和線上購物的成長以及競爭對手之間的激烈競爭，零售商正在轉向巨量資料分析來保持競爭力。
  • 巨量資料被應用於整個零售業務流程，以研究客戶行為、預測需求、改善定價等。當今零售業的許多巨量資料應用都是由系統範圍的成本降低、改善的線上和店內客戶體驗、資料主導的自適應供應鏈以及即時分析和定位所驅動的。
  • 巨量資料分析的使用使產業能夠更了解消費者的行為模式並據此規劃生產計畫。使用來自公共網際網路的巨量資料（例如用戶生成內容 (UGC) 和線上客戶評論 (OCR)資料）為分析零售業客戶行為提供了一種新興選擇。
  • 2022年1月，全球資料分析和消費者情報提供者J.D. Power重新推出了其汽車資料解決方案部門管理的三款關鍵汽車資料產品。這些包括針對車輛識別號碼 (VIN) 描述、庫存管理、數位零售和辦公桌應用的支付和獎勵資料的解決方案。
  • 零售商使用 MapR Technologies 等供應商提供的巨量資料平台來儲存和整合各種線上和線下客戶資料、電子商務交易、點選流資料、電子郵件、社群媒體和客服中心記錄，並進行分析。

亞太地區將經歷最高成長

  • 由於人口的成長和電子商務，亞太地區數位產品和服務產生的資料量激增。巨量資料在亞太地區的國際銀行中被廣泛應用，但越來越多的本地金融機構也開始擁抱巨量資料，以期獲得「後發優勢」。
  • 網際網路使用量的增加使得組織能夠存取大量資料。由於這些優勢，跨國公司現在將巨量資料視為可操作的知識。
  • 最終用戶也正在接受巨量資料分析的外包服務模式。資料分析外包是商務策略，其中資料主導的組織將資料委託給服務提供商，以換取獲取有見地的報告。提供者將建立和維護基礎設施、管理資料並分析資料。管理企業產生的資料非常耗時，而對即時洞察的需求推動了對外包資料分析的需求。
  • 為了容納不斷成長的資料，您必須向叢集添加額外的實體伺服器，這既費時又昂貴。雲端平台的完全可擴充性為企業提供了無限的儲存容量需求。由於這些優勢，雲端平台變得越來越受歡迎。
  • 此外，2023 年 2 月，中國西南地區主要巨量資料中心貴州省宣布計劃在 2023 年投資 200 億元人民幣（29 億美元）用於巨量資料相關計畫。該省省長宣布，將加快建設先進的數位基礎設施，包括5G、運算網路和資料中心。這些發展預計將促進該地區巨量資料技術的發展。

巨量資料技術產業概況

市場集中度較高，IBM、微軟和 SAP 等主要傳統參與者佔據市場主導地位。企業關心員工和客戶資料的隱私和管理，因此他們更信任現有的供應商，而不是新參與企業的供應商。

  • 2022 年 12 月-惠普宣佈為 HPE GreenLake 推出新的應用程式、分析和開發人員服務。邊緣到雲端技術使企業能夠跨混合雲端環境為生產工作負載實施資料優先的現代化計畫。透過來自亞馬遜網路服務(AWS) 的Amazon Elastic Kubernetes Service (Amazon EKS)、基礎設施即程式碼和雲端原生工具鏈，HPE GreenLake for Private Cloud Enterprise 擴展了Kubernetes 的容器部署選項，加速了客戶的DevOps 和持續整合以及持續配置（CI/CD）環境。
  • 2022 年 9 月 – SAS Viya 分析平台在 Microsoft Azure 市場上付費使用制。透過 Microsoft Azure 上功能齊全的 SAS Viya，世界各地的客戶現在可以存取關鍵資料探索、機器學習和模型部署分析。 SAS Viya 配備了廣泛的應用程式內學習中心，可協助您快速入門並取得長期成功，並提供多種翻譯語言。

其他福利：

  • Excel 格式的市場預測 (ME) 表
  • 3 個月的分析師支持

目錄

第 1 章 簡介

  • 研究假設和市場定義
  • 研究範圍

第2章調查方法

第3章執行摘要

第4章 市場洞察

  • 市場概況
  • 產業吸引力－波特五力分析
    • 供應商的議價能力
    • 消費者議價能力
    • 新進入者的威脅
    • 競爭對手之間的競爭
    • 替代品的威脅

第5章 市場動態

  • 市場促進因素與限制因素簡介
  • 市場促進因素
    • 資料發現和視覺化工具的廣泛採用將推動市場成長
  • 市場限制
    • 相關人員和第三方對產生的資料進行駭客攻擊和篡改是市場成長面臨的挑戰

第6章 市場細分

  • 按出貨方式
    • 本地
    • 雲
  • 按最終用戶產業
    • 通訊和 IT
    • 能源和電力
    • BFSI
    • 零售
    • 製造業
    • 航太和國防
    • 工程與建築
    • 醫療保健和製藥
    • 其他行業（運輸和物流、媒體和娛樂）
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
    • 歐洲
      • 英國
      • 德國
      • 法國
    • 亞洲
      • 中國
      • 日本
      • 印度
      • 韓國
    • 澳洲和紐西蘭
    • 拉丁美洲
    • 中東和非洲

第7章 競爭格局

  • 公司簡介
    • IBM Corporation
    • Microsoft Corporation
    • Oracle Corporation
    • SAP SE
    • Hewlett-Packard Company
    • Cisco Systems Inc.
    • SAS Institute
    • Information Builders Inc.
    • MicroStrategy Incorporated
    • Accenture PLC

第8章投資分析

第9章 市場機會與未來趨勢

簡介目錄
Product Code: 50532

The Big Data Technology Market size is estimated at USD 234.27 billion in 2025, and is expected to reach USD 375.76 billion by 2030, at a CAGR of 9.91% during the forecast period (2025-2030).

Big Data Technology - Market - IMG1

Key Highlights

  • Big data technology is defined as software utility. This technology is primarily designed to analyze, process, and extract information from a large data set and a huge set of extremely complex structures.
  • The amount of data produced is rising quickly yearly due to improvements in new technology, gadgets, and communication. The market for big data technologies and services is primarily driven by the demand for actionable insights that can be used for future decision-making processes by evaluating the constantly growing amounts of structured and unstructured data.
  • The automobile sector is positioning itself to be industry 4.0-ready with the rise of industrial IoT and M2M connectivity. Robots, sensors, barcode readers, and RFIDs are now commonplace in this sector's factory floor. Data generation points have drastically risen as a result of these gadgets.
  • Supply and demand factors play a significant role in the consumer electronics business. This industry sector has significantly benefited from big data analytics, allowing it to convert from a push market strategy to a pull market strategy.
  • Furthermore, the enormous amount of data produced and stored makes it vulnerable to hacking and modification by outside parties or insiders. This will jeopardize the safety of any saved data. The vendors of big data technology, whose reputation would be in danger, will be immediately impacted.

Big Data Technology Market Trends

Retail Industry to Dominate the Market

  • With Big Data technologies and sophisticated analytics, the retail sector is undergoing a significant revolution. Retailers are using Big Data analytics to stay competitive due to the growth of e-commerce, online purchasing, and high levels of rivalry.
  • Big Data is used throughout the whole retail process in the business to study customer behavior, forecast demand, and improve prices. Most big data applications in retail today are for system-wide cost reduction, enhancing the customer experience both online and in-store, data-driven adaptive supply chains, and real-time analytics and targeting.
  • With the use of big data analytics, the industry is now more aware of consumer behavior patterns and can plan production based on these. Using big data from the public internet as user-generated content (UGC) or online customer reviews (OCR) data presents an up-and-coming alternative for analyzing retail customer behavior.
  • In January 2022, J.D. Power, a global provider of data analytics and consumer intelligence, relaunched three major automotive data products maintained by the company's Autodata Solutions division. These include solutions for vehicle identification number (VIN) descriptions, inventory management, and payment and incentives data for digital retail and desking applications.
  • Retailers may store, integrate, and analyze a wide range of online and offline customer data, e-commerce transactions, clickstream data, email, social media, and call center records using a big data platform provided by vendors like MapR Technologies.

Asia-Pacific to Witness the Highest Growth

  • Asia-Pacific is seeing a boom in data produced from digital goods and services due to population expansion and increased e-commerce. While big data has been widely used by Asian-Pacific international banks (APAC), more local institutions are increasingly doing the same to achieve a "second-mover advantage."
  • Due to increased Internet usage, organizations can access a vast amount of structured and unstructured data. Due to these advantages, substantial multinational corporations now have their big data evaluated for practical knowledge.
  • End users are also embracing big data analytics outsourcing service models. Data analytics outsourcing is a business strategy where a data-driven organization entrusts a service provider with its data in exchange for access to insightful reporting. The provider handles infrastructure setup and maintenance, data management, and data analysis. The need for immediate insights is driving the need for significant data analytics outsourcing because managing the data generated by enterprises takes time.
  • More physical servers must be added to the cluster to accommodate the growing data, which takes time and money. A cloud platform's complete scalability gives businesses access to limitless storage capacity on demand. As a result of its advantages, the technology is expanding in areas where it is being used.
  • Moreover, In February 2023, Guizhou Province, a major big data hub in southwest China, announced its plan to invest 20 billion yuan (USD 2.9 billion) in big data-related initiatives in 2023. The director of the province announced that the province will accelerate the construction of 5G, computing networks, data centers, and other forms of advanced digital infrastructure. Such developments are expected to boost the growth of big data technology in the region.

Big Data Technology Industry Overview

The market is concentrated, with significant legacy players dominating the market, like IBM, Microsoft, and SAP. Since companies are concerned about the privacy and management of their employee/customer data, they trust established vendors more than new entrants.

  • December 2022 - Hewlett-Packard Company has announced new application, analytics, and developer services for HPE GreenLake. With edge-to-cloud technology, businesses can implement a modernization plan that puts data first for production workloads across hybrid cloud environments. Through Amazon Elastic Kubernetes Service (Amazon EKS) Anywhere from Amazon Web Services (AWS), infrastructure-as-code, and cloud-native toolchains, HPE GreenLake for Private Cloud Enterprise offers expanded container deployment options for Kubernetes to support customers' DevOps and continuous integration and continuous deployment (CI/CD) environments.
  • September 2022 - The SAS Viya analytics platform is now pay-as-you-go on the Microsoft Azure Marketplace. Customers from all over the world have access to vital data exploration, machine learning, and model deployment analytics thanks to full-featured SAS Viya on Microsoft Azure. It features a rich in-app learning center to help both quick onboarding and long-term success, and it is available in many translated languages.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHT

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Force Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Intensity of Competitive Rivalry
    • 4.2.5 Threat of Substitute Products

5 MARKET DYNAMICS

  • 5.1 Introduction to Market Drivers and Restraints
  • 5.2 Market Drivers
    • 5.2.1 Increasing Adoption of Data Discovery and Visualization Tools is Expanding the Market Growth
  • 5.3 Market Restraints
    • 5.3.1 Hacking and Tampering of Generated Data by Insiders or Third Party is Challenging the Market Growth

6 MARKET SEGMENTATION

  • 6.1 By Delivery Mode
    • 6.1.1 On-Premise
    • 6.1.2 Cloud
  • 6.2 By End-user Vertical
    • 6.2.1 Telecom & IT
    • 6.2.2 Energy & Power
    • 6.2.3 BFSI
    • 6.2.4 Retail
    • 6.2.5 Manufacturing
    • 6.2.6 Aerospace & Defense
    • 6.2.7 Engineering & Construction
    • 6.2.8 Healthcare & Pharmaceuticals
    • 6.2.9 Other End -user Verticals (Transportation & Logistics, Media & Entertainment)
  • 6.3 By Geography
    • 6.3.1 North America
      • 6.3.1.1 United States
      • 6.3.1.2 Canada
    • 6.3.2 Europe
      • 6.3.2.1 United Kingdom
      • 6.3.2.2 Germany
      • 6.3.2.3 France
    • 6.3.3 Asia
      • 6.3.3.1 China
      • 6.3.3.2 Japan
      • 6.3.3.3 India
      • 6.3.3.4 South Korea
    • 6.3.4 Australia and New Zealand
    • 6.3.5 Latin America
    • 6.3.6 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 IBM Corporation
    • 7.1.2 Microsoft Corporation
    • 7.1.3 Oracle Corporation
    • 7.1.4 SAP SE
    • 7.1.5 Hewlett-Packard Company
    • 7.1.6 Cisco Systems Inc.
    • 7.1.7 SAS Institute
    • 7.1.8 Information Builders Inc.
    • 7.1.9 MicroStrategy Incorporated
    • 7.1.10 Accenture PLC

8 INVESTMENT ANALYSIS

9 MARKET OPPORTUNITIES AND FUTURE TRENDS