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1435869

自主資料平台：市場佔有率分析、產業趨勢與統計、成長預測（2024-2029）

Autonomous Data Platform - 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

自主資料平台市場規模預計到 2024 年為 17.7 億美元，預計到 2029 年將達到 44.6 億美元，在預測期內（2024-2029 年）市場規模將增加 203.3 億美元。複合年成長率為 % 。

自主數據平台-市場

認知運算技術和進階分析的日益採用，以及複雜和非結構化資料的增加正在推動市場成長。在世界各地，人們正在交換未來幾年將不斷發展的資訊。 Domo Inc. 估計，到 2020年終，地球上每個人每秒將產生 1.7 MB 的資料。此外，中小企業對自主資料平台的需求不斷成長以及雲端技術的加速採用是該市場成長的決定因素。

主要亮點

  • 事實證明，巨量資料是當今企業廣泛使用的技術之一。自主資料平台控制和最佳化巨量資料基礎設施。根據Salesforce最新的購物指數，2018年與前一年同期比較位商務年增13%，預計2020年零售電商銷售額將超過4兆美元。美國人口普查局報告稱，2019 年，87% 的美國客戶在數位管道上發起搜尋，高於前一年的 71%。這就需要加強雲端巨量資料服務的使用。
  • 該技術提供的優勢正在加速雲端運算的採用。根據《富比士》預測，到 2020 年，雲端運算市場規模預計將增至 1,600 億美元，實現 19% 的成長率。預計雲端基礎的部署在預測期內將顯著成長。雲端平台提供的增強協作、可擴展性和成本效益預計將推動對雲端基礎的自主資料平台的需求。
  • 網際網路的普及將增加設備和自主資料工具的數量。這種資料成長的主要原因是網路。根據思科VNI報告，到2022年，將有約48億網路用戶，即世界人口的60%。資料消費量成長的另一個關鍵因素是全球平均 Wi-Fi 速度的上升，根據思科 VNI全球IP 流量預測，2022 年亞太地區的 Wi-Fi 速度將比 2017 年增加一倍以上。
  • 然而，複雜的分析過程、缺乏熟練和訓練有素的專業人員以及與維持品質和安全同步相關的問題是限制該市場成長的因素。此外，認知運算技術的日益普及以及對高階分析的需求不斷成長為市場成長提供了充足的機會。
  • 推動 COVID-19 疾病對巨量資料分析產業乃至自主資料平台市場影響成長的主要因素是數位轉型需求的增加、分析投資的增加、遠端服務和位置資料的需求，以及對真實資料的需求。時間資訊追蹤並監測 COVID-19 疾病的傳播。
  • 特別是在 COVID-19感染疾病期間，近乎即時地提取、可視化這些情報並根據這些情報採取行動的需求變得越來越關鍵，包括努力阻止傳播並幫助企業生存。這正在成為一個目標，並且正在成為現實受到鼓勵。

自主資料平台市場趨勢

零售業預計將顯著成長

  • 隨著網路使用的增加，零售業變得更加以客戶為中心。科技的進步也正在加速該產業消費者行為的改變。因此，自主資料平台已成為零售業的重要組成部分，幫助零售商在競爭激烈的市場中提高客戶忠誠度。該平台幫助零售商即時追蹤客戶的購物旅程，使零售商能夠了解並滿足客戶的需求和要求。
  • 巨量資料為人工智慧提供動力，因此人工智慧將繼續進軍零售和消費品產業。世界各地的許多巨量資料公司聲稱可以幫助負責人、零售商和電子商務公司管理他們的資料，以便他們能夠個人化客戶參與、預測庫存並區隔區域內的客戶行為。
  • MapR Technologies 提供了一個自主數據平臺，可説明零售商存儲、集成和分析電子商務、銷售點 （POS） 系統、點擊流數據、電子郵件、社交媒體和電話，以獲取各種線上和線下客戶數據。 中心記錄 - 所有內容都在一個中央存儲庫中。 沃爾瑪正在經歷數字化轉型。 目前，世界上最大的私有雲系統正在開發中，據說每小時能夠管理2.5PB的數據。
  • 據 IBM 稱，62% 的零售商表示，使用巨量資料可以提供競爭優勢。預計在預測期內，該行業對巨量資料技術的採用將顯著增加，從而對自主資料平台市場的成長產生積極影響。
  • 零售業需要強大的自主資料平台來即時收集各種來源的各種類型的資料，包括結構化和非結構化資料。該行業面臨的重大課題包括對全通路體驗和消費者即時追蹤的需求。由於自主資料平台和服務有助於有效應對這些課題，預計未來幾年零售商對它們的採用將會增加。

北美佔最大市場佔有率

  • 網路和行動裝置在北美的廣泛普及為公司接觸該地區的通路合作夥伴、客戶和其他相關人員創造了可能性。用於與業務合作夥伴和客戶建立聯繫並提供適合客戶業務需求的內容的行動裝置和社群媒體平台的普及促使企業採用自主資料平台和服務。
  • 美國跨國公司英特爾看到了巨量資料的巨大價值。該公司利用巨量資料更快開發晶片、識別製造缺陷並通報安全威脅。透過採用巨量資料，該公司能夠促進預測分析，並在提高品質的同時節省約 3000 萬美元的品質保證支出。白宮也投資約2億美元用於巨量資料計劃。此外，該國在所研究的市場中擁有大量專業人士，並且在預測期內具有巨大的成長潛力。
  • 預計美國零售商的增長將推動對供應鏈管理的投資，他們熱衷於改善客戶體驗。 大數據應用程式和自主數據平臺可以幫助您實現這兩項目標。 根據美國商務部發佈的季度電子商務統計數據，2019年客戶在美國賣家的在線消費為6017.5億美元，比上一年的5236.4億美元增長了14.9%，高於2018年報告的在線銷售額。 商務部同比增長13.6%。 因此，預計美國零售商對大數據的使用以及自主數據平臺的使用也將顯著增加。
  • 公司使用基於機器學習技術的軟體和服務來提供最可靠的最終用戶體驗，並專注於提供最好的服務。他們利用自主資料平台來分析客戶相關資料並發現客戶購買行為、季節性需求和產品需求等參數。隨著獨立資料平台的出現，負責人可以將各種來源的客戶資料集中到一個平台中，從而節省整合工作的時間。

自主資料平台產業概況

自主資料平台市場主要由 IBM、微軟和 Teradata Corporation 等主要傳統廠商主導。企業關心員工和客戶資料的隱私和控制，因此他們信任現有供應商而不是新進入者。資料的激增正在推動 Oracle、MapR 和 AWS 等資料管理平台供應商開發和設計自主資料平台，幫助 IT 團隊簡化和管理流程。自主資料平台的提供者正在相互競爭，以擴大其市場範圍並增加在新市場的影響力。

  • 2020 年 6 月 - 領先的 Python資料科學平台供應商 Anaconda, Inc. 與 IBM Watson 宣佈建立新的合作夥伴關係，以簡化企業對 AI開放原始碼技術的採用。透過合作，兩家公司計劃促進創新並解決許多公司面臨的人工智慧和資料科學技能差距。 Anaconda Team Edition 儲存庫與 IBM Cloud Pak for Data 上的 IBM Watson Studio 整合，使組織能夠更好地管理和加速跨任何雲端的 AI開放原始碼技術的採用。
  • 2020 年 2 月 - Oracle宣布推出 Oracle 雲端資料科學平台。其核心是Oracle雲端基礎設施資料科學，幫助企業協作建置、訓練、管理和部署機器學習模型，加速資料科學計劃的成功，提供共用計劃、模型目錄和團隊安全策略、可重複性和審核。

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章市場動態

  • 市場概況
  • 市場促進因素
    • 擴大採用認知運算技術和進階分析
    • 由於互連設備和社群媒體的顯著成長，非結構化資料量不斷增加
  • 市場限制因素
    • 複雜的分析過程需要熟練專業人員的服務
  • 產業吸引力－波特五力分析
    • 新進入者的威脅
    • 買方議價能力
    • 供應商的議價能力
    • 替代產品的威脅
    • 競爭公司之間的敵意強度
  • 產業價值鏈分析
  • COVID-19疾病對自主資料平台市場的影響分析

第5章市場區隔

  • 依組織規模
    • 主要企業
    • 中小企業
  • 依部署類型
    • 公共雲端
    • 私有雲端
    • 混合雲端
  • 依行業 依最終用戶
    • BFSI
    • 醫療保健和生命科學
    • 零售和消費品
    • 媒體和通訊
    • 其他最終用戶產業（政府、製造業）
  • 地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東和非洲

第6章 競爭形勢

  • 公司簡介
    • Oracle Corporation
    • International Business Machines Corporation
    • Amazon Web Services
    • Teradata Corporation
    • Qubole Inc
    • MapR Technologies, Inc.
    • Alteryx Inc.
    • Ataccama Corporation
    • Cloudera, Inc.
    • Gemini Data Inc.
    • Datrium, Inc.
    • Denodo Technologies
    • Paxata, Inc.
    • Zaloni Inc.

第7章 投資分析

第8章市場機會及未來趨勢

簡介目錄
Product Code: 70342

The Autonomous Data Platform Market size is estimated at USD 1.77 billion in 2024, and is expected to reach USD 4.46 billion by 2029, growing at a CAGR of 20.33% during the forecast period (2024-2029).

Autonomous Data Platform - Market

The growing adoption of cognitive computing technology and advanced analytics as well as the rising volume of complex and unstructured data drive market growth. Across the world, people are swapping information that is going to develop in the coming years. Domo Inc. estimated that 1.7MB of data will be created every second for every person on earth by 2020 end. Additionally, rising demand for autonomous data platforms from SMEs and accelerating adoption of cloud technology are the determinants for the growth of this market.

Key Highlights

  • Big Data has turned out to be one of the widespread technologies being utilized by companies today. An autonomous data platform controls and optimizes the big data infrastructure. According to the most contemporary Shopping Index of Salesforce, digital commerce grew at a rate of 13% year-over-year in Q4 2018, and projected retail e-commerce sales exceeding USD 4 trillion through 2020. The US Census Bureau reported that 87% of the US customers began their hunt in digital channels in 2019, up from 71% the previous year. This calls for enhanced use of big data services for the cloud.
  • Owing to the advantages the technology grants, cloud computing is witnessing an accelerated development in its adoption. According to Forbes, the market for cloud computing will increase to USD 160 billion by 2020, achieving a growth rate of 19%. Cloud-based deployment anticipated to have meaningful growth during the forecast period. Enhanced collaboration, Scalability, and cost-effectiveness offered by the cloud platform are expected to encourage the demand for cloud-based autonomous data platforms.
  • The propagation of the Internet will feed this increase in the number of devices and autonomous data tool. The Internet happens to the principal reason for this growth in data. According to the Cisco VNI report, there will be about 4.8 billion internet subscribers in 2022, 60% of the global population. According to Cisco VNI Global IP Traffic Forecast, the other significant factor for the increase in consumption of data will be the rise in global average Wi-Fi speeds that are exacted to more than double in Asia-Pacific in 2022 as compared to 2017.
  • However, complicated analytical process, lack of skilled and trained professional, and problem associated with the maintaining sync between quality and safety acts as a restricting factor for this market growth. Moreover, growing popularity of cognitive computing technology and the increasing need for advanced analytics will provide adequate opportunities for the growth of the market.
  • The principal factors driving the growth of COVID-19 impact on the Big Data Analytics industry and hence Autonomous Data Platform Market are increasing demand for digital transformation, increased investments in analytics, growing demand for remote services and location data, and increasing need for real-time information track and monitor the COVID-19 spread.
  • Especially during the COVID-19 pandemic - including efforts to contain its spread and help businesses stay afloat - the need to extract, visualize, and execute this intelligence in near-real-time is increasingly becoming a mission-critical objective, thus giving a boost to the Autonomous Data Platform Market.

Autonomous Data Platform Market Trends

Retail Vertical is Expected to Register a Significant Growth

  • With the growing use of the Internet, the retail vertical has become more customer-centric. Advancements in technologies have also made this vertical witness the accelerated changes in consumers' behavior. Consequently, the autonomous data platform has become an essential part of the retail vertical, assisting retailers to attain improved customer loyalty in the highly competitive market. The platform helps retailers track customers' shopping journeys in real-time, thus enabling retailers to understand and address their customers' needs and requirements.
  • Big data powers AI, and so it follows that AI would continue to find its way into the retail & consumer goods industry. Many big data companies globally claim to assist marketers, retailers, and eCommerce companies in managing their data so that it would allow them to personalize customer engagement, forecast inventory, and segment customers in the region.
  • MapR Technologies is offering an Autonomous Data Platform, which helps retailers store, integrate, and analyze the wide variety of online and offline customer data e-commerce transactions, point of sale (POS) systems, clickstream data, email, social media, and call center records - all in one central repository. Walmart is experiencing a digital transformation. It is in the process of developing the world's most extensive private cloud system, which is supposed to have the capacity to manage 2.5 petabytes of data every hour.
  • According to IBM, 62% of retailers report that the use of Big Data is giving them a competitive advantage. It is expected that the industry will witness significant growth in the adoption of Big Data technology over the forecast period, thereby positively impacting the Autonomous Data Platform market's growth.
  • The retail sector needs a strong autonomous data platform to collect different data types, including structured and unstructured, from various sources in real-time. The significant challenges faced by this vertical include the demand for omnichannel experience and the tracking of consumers in real-time. As autonomous data platforms and services help efficiently address these challenges, their adoption by retailers is expected to increase in the coming years.

North America to Hold the Largest Market Share

  • The extensive penetration of the Internet and mobile devices in North America has created possibilities for enterprises to reach out to channel partners, clients, and other stakeholders in the region. The widespread use of mobile devices and social media platforms to connect with business partners and clients for giving customized content as per the business necessities of clients has prompted businesses to embrace autonomous data platforms and services.
  • American multinational corporation, Intel is finding meaningful value in big data. The firm uses big data to develop chips quicker, recognize manufacturing glitches, and inform about security threats. By adopting Big Data, the firm has been able to facilitate predictive analysis and save around USD 30 million on its Quality Assurance spend while still increasing quality. The White House has also invested around USD 200 million in big data projects. The country also has a huge number of professionals in the studied market, which offers a vast potential to grow over the forecast period.
  • The US retailer's growth is expected to foster their investment in the supply chain management and are rigorously trying to enhance the customer experience. Big data applications and Autonomous data platform can help them in achieving both. Customers spent USD 601.75 billion online with U.S. merchants in 2019, up 14.9% from USD 523.64 billion the prior year, according to the U.S. Department of Commerce quarterly ecommerce figures released, and that was a higher growth rate than 2018, when online sales reported by the Commerce Department rose 13.6% year over year. As a result, the use of big data and hence Autonomous data platform is also expected to rise significantly among the US retailers.
  • Companies focus on offering the most reliable end-user experience and providing the best services by using machine-learning technology-based software and services. They leverage the autonomous data platform to analyze customer-related data and to find parameters such as customers' buying behavior, seasonal demand, and product demand. With the advent of independent data platforms, marketers can centralize customers' data from different sources at one platform, thereby saving hours of integration work.

Autonomous Data Platform Industry Overview

The Autonomous Data Platform Market is concentrated with major legacy players dominating the market like IBM, Microsoft, and Teradata Corporation. Since companies are concerned regarding the privacy and management of their employee/customer data, they trust established vendors more rather than new entrants. The proliferation of data has pushed data management platform vendors, such as Oracle, MapR, and AWS, to develop and design autonomous data platforms that help IT teams simplify and manage processes. The autonomous data platform providers are competing with each other to expand their market coverage and increase their presence in newer markets.

  • June 2020 - Anaconda, Inc. provider of the leading Python data science platform and IBM Watson announced a new collaboration to help simplify enterprise adoption of AI open-source technologies. By working together, the two companies plan to help fuel innovation and address the AI and data science skills gap that many enterprises face. Anaconda Team Edition repository will be integrated with IBM Watson Studio on IBM Cloud Pak for Data, enabling organizations to better govern and speed the deployment of AI open-source technologies across any cloud.
  • Feb 2020 - Oracle announced the availability of the Oracle Cloud Data Science Platform. At the core is Oracle Cloud Infrastructure Data Science, helping enterprises to collaboratively build, train, manage and deploy machine learning models to increase the success of data science projects, helping improve the effectiveness of data science teams with capabilities like shared projects, model catalogs, team security policies, reproducibility and auditability.

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 DYNAMICS

  • 4.1 Market Overview
  • 4.2 Market Drivers
    • 4.2.1 Growing Adoption of Cognitive Computing Technology and Advanced Analytics
    • 4.2.2 Expanding Volume of Unstructured Data Due to the Phenomenal Growth of Interconnected Devices and Social Media
  • 4.3 Market Restraints
    • 4.3.1 Complex Analytical Process Requiring Skilled Professionals Services
  • 4.4 Industry Attractiveness - Porter's Five Force Analysis
    • 4.4.1 Threat of New Entrants
    • 4.4.2 Bargaining Power of Buyers/Consumers
    • 4.4.3 Bargaining Power of Suppliers
    • 4.4.4 Threat of Substitute Products
    • 4.4.5 Intensity of Competitive Rivalry
  • 4.5 Industry Value Chain Analysis
  • 4.6 Analysis on the impact of COVID-19 on the Autonomous Data Platform Market

5 MARKET SEGMENTATION

  • 5.1 By Organization Size
    • 5.1.1 Large Enterprises
    • 5.1.2 Small and Medium-Sized Enterprise
  • 5.2 By Deployment Type
    • 5.2.1 Public Cloud
    • 5.2.2 Private Cloud
    • 5.2.3 Hybrid Cloud
  • 5.3 By End-user Vertical
    • 5.3.1 BFSI
    • 5.3.2 Healthcare and Life Sciences
    • 5.3.3 Retail and Consumer Goods
    • 5.3.4 Media and Telecommunication
    • 5.3.5 Other End-User Verticals (Government, Manufacturing)
  • 5.4 Geography
    • 5.4.1 North America
    • 5.4.2 Europe
    • 5.4.3 Asia Pacific
    • 5.4.4 Latin America
    • 5.4.5 Middle East & Africa

6 COMPETITIVE LANDSCAPE

  • 6.1 Company Profiles
    • 6.1.1 Oracle Corporation
    • 6.1.2 International Business Machines Corporation
    • 6.1.3 Amazon Web Services
    • 6.1.4 Teradata Corporation
    • 6.1.5 Qubole Inc
    • 6.1.6 MapR Technologies, Inc.
    • 6.1.7 Alteryx Inc.
    • 6.1.8 Ataccama Corporation
    • 6.1.9 Cloudera, Inc.
    • 6.1.10 Gemini Data Inc.
    • 6.1.11 Datrium, Inc.
    • 6.1.12 Denodo Technologies
    • 6.1.13 Paxata, Inc.
    • 6.1.14 Zaloni Inc.

7 INVESTMENT ANALYSIS

8 MARKET OPPORTUNITIES AND FUTURE TRENDS