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市場調查報告書
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1403761

巨量資料技術：市場佔有率分析、產業趨勢與統計、2024年至2029年成長預測

Big Data Technology - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts 2024 - 2029
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預計到2024年為2,131.5億美元，預計到2029年將達到3,419.3億美元，在預測期內（2024-2029年）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實用程式。該技術主要旨在從大型資料集和大量高度複雜的結構中分析、處理和提取資訊。
  • 隨著新技術、小工具和通訊的進步，產生的資料量每年都在迅速增加。巨量資料技術和服務市場主要是由對可操作見解的需求所驅動的，透過評估不斷成長的結構化和非結構化資料，可以在未來的決策流程中利用這些見解。
  • 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 現在在該行業的工廠車間中已司空見慣。由於這些小工具的出現，資料生成點呈指數級成長。
  • 供需因素在消費性電子業務中扮演重要角色。該行業極大地受益於巨量資料分析，實現了從推式市場策略轉向拉動式市場策略的轉變。
  • 此外，產生和儲存的大量資料很容易受到外部和相關人員的駭客攻擊和篡改。這會損害儲存資料的安全性。聲譽受到威脅的巨量資料技術供應商將立即受到影響。
  • 在 COVID-19 期間，遠距工作的增加刺激了雲端基礎的分析的採用，但雲端中資料量的增加引發了複雜的隱私問題。組織現在正在應對巨量資料技術，這些技術可以增強供應鏈管理並幫助了解客戶行為的變化。

巨量資料技術市場趨勢

零售業主導市場

  • 由於採用巨量資料技術和高階分析，零售業正經歷重大變革時期。由於電子商務和線上購買的成長以及競爭對手之間的高度對抗關係，零售公司正在利用巨量資料分析來保持競爭力。
  • 巨量資料應用於企業的整個零售流程，包括研究客戶行為、預測需求和改善價格。當今零售業中的許多巨量資料用途包括降低系統範圍的成本、改善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。
  • 巨量資料分析的使用使該行業能夠更加了解消費者的行為模式並相應地生產計畫。使用來自公共網際網路的巨量資料作為用戶生成內容 (UGC) 和線上客戶評論 (OCR)資料，為分析零售業的客戶行為提供了一種新興的選擇。
  • 2022 年 1 月，全球資料分析和消費者情報提供者 JD Power 重新推出了由該公司資料 Solutions 部門管理的三款主要汽車資料產品。其中包括用於數位零售和辦公桌應用的車輛識別號碼 (VIN) 描述、庫存管理、支付和獎勵資料解決方案。
  • 零售商使用MapR Technologies等供應商的巨量資料平台來儲存和整合廣泛的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，可以進行分析。
巨量資料技術-市場-IMG2

亞太地區將經歷最高成長

  • 在亞太地區，由於人口成長和電子商務的增加，數位商品和服務產生的資料正在迅速增加。巨量資料在亞太地區（APAC）被國際銀行廣泛應用，但更多本土金融機構也在做同樣的事情，以獲得「第二秒優勢」。
  • 網際網路使用的增加使組織能夠存取大量資料。由於這些好處，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。資料分析外包是一種業務策略，其中資料主導的組織將資料委託給服務提供商，以換取獲得富有洞察力的報告的機會。提供者負責基礎設施設置和維護、資料管理和資料分析。管理企業產生的資料需要時間，而對即時洞察的需求正在推動外包資料分析的需求。
  • 為了適應不斷成長的資料，您必須向叢集添加實體伺服器，這既耗時又昂貴。雲端平台的全面可擴充性為企業提供無限的按需儲存容量。由於其優勢，雲端平台變得越來越普遍。
  • 此外，2023 年 2 月，中國西南部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）用於巨量資料相關措施。工信部負責人宣布，國家將加速5G、運算網路、資料中心等先進數位基礎建設。這些發展預計將支持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，IBM、微軟和 SAP 等重要傳統廠商佔據市場主導地位。企業關心員工和客戶資料的隱私和控制，因此他們更信任現有供應商而不是新參與企業。

  • 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。透過其Amazon Elastic Kubernetes Service (Amazon EKS) Anywhere、基礎設施即程式碼以及Amazon Web Services (AWS) 上的雲端原生工具鏈，適用於私有雲企業的HPE GreenLake 擴展了Kubernetes 容器部署選項，並協助客戶改善其開發營運和持續營運整合和持續配置(CI/CD) 環境。
  • 2022 年 9 月 - SAS Viya 分析平台在 Microsoft Azure Marketplace 中付費使用制。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 具有廣泛的應用程式內學習中心，可支援快速部署和長期成功，並提供多種翻譯語言版本。

其他福利：

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

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

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
    • 競爭公司之間的敵對關係
    • 替代品的威脅

第5章市場動態

  • 市場促進因素與市場抑制因素介紹
  • 市場促進因素
    • 由於資料發現和視覺化工具的採用增加，市場成長不斷擴大
  • 市場抑制因素
    • 內部人員和第三方對產生資料的駭客攻擊和篡改是市場成長的挑戰

第6章市場區隔

  • 依提供方式
    • 本地
    • 雲
  • 按最終用戶產業
    • 通訊/IT
    • 能源/電力
    • BFSI
    • 零售
    • 製造業
    • 航太/國防
    • 工程與建築
    • 醫療保健與製藥
    • 其他行業（交通/物流、媒體/娛樂）
  • 按地區
    • 北美洲
      • 美國
      • 加拿大
    • 歐洲
      • 英國
      • 德國
      • 法國
      • 其他歐洲國家
    • 亞太地區
      • 中國
      • 日本
      • 印度
      • 韓國
      • 其他亞太地區
    • 拉丁美洲
    • 中東/非洲

第7章競爭形勢

  • 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 市場機會及未來趨勢

簡介目錄
Product Code: 50532
Big Data Technology - Market - IMG1

The Big Data Technology Market size is estimated at USD 213.15 billion in 2024, and is expected to reach USD 341.93 billion by 2029, growing at a CAGR of 9.91% during the forecast period (2024-2029).

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.
  • With the rise of remote work during Covid-19, there was a boost in the adoption of cloud-based analytics, which presents complex privacy concerns due to increased data volume on the cloud. Organizations now reply on big data technology, which helps them to enhance their supply chain management and understand the shift in customer behavior.

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.
Big Data Technology - Market - IMG2

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
      • 6.3.2.4 Rest of Europe
    • 6.3.3 Asia Pacific
      • 6.3.3.1 China
      • 6.3.3.2 Japan
      • 6.3.3.3 India
      • 6.3.3.4 South Korea
      • 6.3.3.5 Rest of Asia-Pacific
    • 6.3.4 Latin America
    • 6.3.5 Middle East & 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