查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
全球自主數據平台市場:預測至2028年——按組件(服務和平台)、部署(雲端,本地)、企業(SME,企業)、最終用戶,地區分析
市場調查報告書
商品編碼
1218895

全球自主數據平台市場:預測至2028年——按組件(服務和平台)、部署(雲端,本地)、企業(SME,企業)、最終用戶,地區分析

Autonomous Data Platform Market Forecasts to 2028 - Global Analysis By Component (Services and Platform), Deployment (Cloud and On-premises), Enterprise (Small and Medium Enterprise (SME) and Large Enterprise), End User and Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 175+ Pages | 商品交期: 2-3個工作天內

價格

根據Stratistics MRC，2022年全球自主數據平台市場規模將達到9.6963億美元，2028年將達到36.6351億美元，預測期內預計將以複合年增長率24.8%成長。

自主數據工具檢查特定客戶的大數據基礎架構，以解決關鍵業務問題並確保最佳數據庫利用率。 一個自我管理和優□□化的數據和分析平台，利用多個認知計算平台，如 AI 和機器學習 (ML)。 結合啟發式和機器學習，為用戶提供洞察力、可操作的警報和建議，以實現更高的性能、工作負載連續性和成本節約。 它提高了操作效率並簡化了程序。

根據 Salesforce 最新的購物指數，電子商務在 2018 年第四季度同比增長 13%，預計到 2020 年零售電子商務銷售額將超過 4 萬億美元。

市場動態

促進因素

新時代的企業正在採用私有雲和混合雲

由於新時代企業組織的雲利用趨勢以及企業數據存儲的增加，主要是在混合雲端和公共雲端中，自主數據平台的使用在基於雲的企業中持續增長。 此外，與傳統企業數據倉庫系統相比，自治數據平台提供了更多方式來更安全、更快速地探索、共享和集成關鍵數據。

抑制因素

自治數據基礎架構的高成本

隨著技術的進步，企業的期望也在進步。 因此，這些公司經常更新他們基於雲端和以客戶為中心的解決方案，以滿足他們的客戶數據收集、分析和分類要求。 此外，企業將不得不進行大量投資以採用基於雲的自主數據平台，這可能會限制預測期內對這些平台的需求。

機會

對自主數據平台優勢的認識不斷提高

自主數據平台可讓您加密數據、跟蹤工作負載並監控任何試圖訪問您數據的實體。 因此，這些平台使企業可以使用數據，而不必擔心不合適的環境會導致監管或聲譽受損。 此外，這些系統提供了極大的靈活性，允許企業根據便利性和要求增加或減少容量。

威脅

專業人員短缺

存在阻礙市場擴展的限制和困難，例如復雜且昂貴的集成、有限的支持和定制。 市場限制可能是由於缺乏高素質工人和困難的分析程序等因素造成的。 然而，困難的分析方法、缺乏合格和訓練有素的人員以及與質量和安全之間的平衡有關的問題阻礙了市場的擴展。

COVID-19 的影響

COVID-19 大流行的爆發影響了自主數據平台市場，預計該行業的增長將在大流行後得到推動。 這是由於全球 COVID-19 感染率上升，以及公司採用在家工作模式來保護員工免受致命病毒的侵害。 因此，許多公司都在大力投資自主數據平台解決方案，以簡化其整體業務運營並提高生產力。 此外，大流行期間網絡依賴性和網絡負載的增加將推動自主數據平台行業的擴張。

預計在預測期內雲端部分將是最大的部分

據估計，雲端部分的增長利潤豐厚。 由於基於雲端的解決方案的靈活性和成本效益，用戶更可能喜歡並採用它們。 雲端計算平台提供高可擴展性、低入門成本和持續發展。 部署基於雲端的解決方案通過其虛擬環境簡化了服務交付，使組織能夠隨時從互連設備訪問信息。 用戶無需將數據本地存儲在設備上，而是可以通過網路將其上傳到鏈接的設備。 雲端採用帶來的這些優勢將推動該細分市場的增長。

預計在預測期內，中小企業部門的複合年增長率最高。

由於對機器學習等先進技術的投資增加、AI 技術的應用擴大以及數位支付系統的使用增加，預計在預測期內，中小企業細分市場將以最快的複合年增長率增長。 由於數量不斷增加，預計中小型組織將增加對獨立數據結構的需求。 隨著機器學習和人工智能被更頻繁地用於改進決策制定，自主數據平台市場將會增長。

份額最高的地區

在採用尖端技術和基於雲端的解決方案方面，北美被認為是最先進的地區，因為它擁有加拿大和美國等最發達的經濟體，因此預計將佔據最大的市場份額. 在北美，越來越多地使用手機和互聯網正在推動該行業的顯著增長。 此外，越來越多地使用智能手機和數字網站與業務合作夥伴和客戶互動，也有助於該地區的市場擴張。

複合年增長率最高的地區

由於越來越多地使用人工智能和機器學習來支持決策制定，預計亞太地區在預測期內的複合年增長率最高。 此外，組織將來自多個來源的客戶數據合併到統一平台的能力減少了計算工作時間，推動了對自主數據平台的需求。 由於為提高這些平台的能力而增加的研發活動支出，自主數據平台業務有望看到新的增長前景。 因此，預計在預測期內，亞太地區的自治數據庫平台勢頭強勁。

主要發展

2021 年 9 月，Alteryx 與機器人過程自動化軟件公司 UiPath 建立了合作夥伴關係。 通過此次合作，兩家公司共同開發了一種新的連接器，允許 Alteryx 用戶調用 UiPath 機器人並將 UiPath 的 RPA 功能集成到他們的工作流程中。

2021 年 1 月，Alteryx 與 Snowflake 合作開發數據雲端。 該合作夥伴關係將把 Alteryx 的分析自動化和數據科學功能集成到 Snowflake 平台中。 這種集成將為客戶提供自動化數據管道、快速數據處理和大規模加速分析結果。

2020 年 12 月，AWS 與 BlackBerry 的子公司 BlackBerry QNX 建立了合作夥伴關係。 通過此次合作，兩家公司將共同打造智能汽車數據平台 BlackBerry IVY。 此外，BlackBerry IVY 是一個可擴展的雲連接軟件平台，使汽車製造商能夠在車輛本地和雲端安全地讀取、集中並持續提供來自車輛傳感器數據的可操作見解。

2020 年 10 月，IBM 與美國跨國集團控股公司 AT&T 結盟。 通過此次合作，兩家公司推出了混合雲，以更好地管理低延遲私有蜂窩網絡邊緣環境中的開放式混合雲計算。

2020 年 2 月，Oracle 宣布推出 Oracle 雲數據科學平台。 其核心是 Oracle Cloud Infrastructure Data Science，可幫助企業協作構建、訓練、管理和部署機器學習模型，以提高其數據科學項目、共享項目、模型目錄以及安全策略、可重複性等團隊功能的成功率和可審計性，以幫助提高數據科學團隊的效率。

2019 年 6 月，Qubole 宣布了一個自助服務平台，供數據科學家和工程師在他們選擇的公共雲上構建人工智能、機器學習和分析流程。

2019 年 4 月，MapR 宣布了 MapR 數據平台的創新，包括與 Kubernetes 關鍵組件的新深度集成，用於 Spark 和 Drill 上的關鍵工作負載。 由於這項創新，該平台可以更好地管理高彈性的工作負載。

本報告的內容

  • 評估區域和國家級細分市場的市場份額
  • 向新進入者提出戰略建議
  • 2020、2021、2022、2025 和 2028 年的綜合市場數據
  • 涵蓋市場趨勢（市場促進因素、促進因素、機遇、威脅、挑戰、投資機會、建議）
  • 根據市場預測在關鍵業務領域提出戰略建議
  • 競爭格局映射主要共同趨勢
  • 公司簡介，包括詳細的戰略、財務狀況和近期發展
  • 映射最新技術進步的供應鏈趨勢

免費定制服務

訂閱此報告的客戶將免費獲得以下自定義選項之一。

  • 公司簡介
    • 其他市場參與者的綜合概況（最多 3 家公司）
    • 主要參與者的 SWOT 分析（最多 3 家公司）
  • 區域細分
    • 根據客戶要求對主要國家/地區的市場進行估算、預測和復合年增長率（注意：基於可行性檢查。）
  • 競爭基準
    • 根據產品組合、地域分佈和戰略聯盟對主要參與者進行基準測試

目次

第 1 章執行摘要

第 2 章前言

  • 概覽
  • 利益相關者
  • 調查範圍
  • 調查方法
    • 數據挖掘
    • 數據分析
    • 數據驗證
    • 研究方法
  • 調查來源
    • 主要研究資訊來源
    • 二次研究資訊來源
    • 假設

第 3 章市場趨勢分析

  • 促進因素
  • 抑制因素
  • 機會
  • 威脅
  • 最終用戶分析
  • 新興市場
  • COVID-19 的影響

第 4 章波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭公司之間的敵對關係

第 5 章全球自主數據平台市場：按組件分類

  • 服務
    • 諮詢
    • 支持和維護
    • 整合
  • 平台

第 6 章全球自主數據平台市場：按部署

  • 雲端
  • 本機

第 7 章全球自主數據平台市場：按公司分類

  • 中小型企業 (SME)
  • 大企業

第 8 章全球自主數據平台市場：最終用戶

  • 銀行、金融服務和保險 (BFSI)
  • 醫療保健和生命科學
  • 媒體和傳播
  • 零售和消費品
  • 其他最終用戶
    • 能源和公用事業
    • 旅遊和款待
    • 運輸/物流

第 9 章全球自主數據平台市場：按地區

  • 北美
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 意大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳大利亞
    • 新西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中東和非洲
    • 沙特阿拉伯
    • 阿拉伯聯合酋長國
    • 卡塔爾
    • 南非
    • 其他中東地區

第 10 章主要發展

  • 合同、夥伴關係、協作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第 11 章公司簡介

  • Oracle Corporation
  • Hewlett Packard Enterprise Development LP
  • Amazon Web Services, Inc.
  • Teradata
  • IBM
  • Denodo Technologies
  • Alteryx, Inc.
  • Gemini Data
  • Cloudera, Inc.
  • Qubole, Inc.
  • Paxata, Inc.
  • Zaloni Inc.
  • Ataccama Corporation
  • MapR Technologies, Inc.
  • Intellias Ltd.
Product Code: SMRC22431

According to Stratistics MRC, the Global Autonomous Data Platform Market is accounted for $969.63 million in 2022 and is expected to reach $3663.51 million by 2028 growing at a CAGR of 24.8% during the forecast period. The autonomous data tool examines a specific customer's big data infrastructure in order to address critical business issues and assure optimal database utilisation. It is a data and analytics platform that manages and optimises itself by leveraging multiple cognitive computing platforms such as AI and Machine Learning (ML). It provides insights, actionable alerts, and recommendations to users by combining heuristics with machine learning, resulting in high performance, workload continuity, and cost savings. It improves operating efficiency and simplifies the procedure.

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.

Market Dynamics:

Driver:

New-age enterprises are witnessing higher adoption of private and hybrid cloud

Because of the developing trends of cloud application in new-age businesses organisations, and storage of enterprise data primarily in hybrid and public clouds, the applications of autonomous data platforms are continually increasing in cloud-based businesses. Furthermore, autonomous data platforms offer numerous means for examining, sharing, and integrating essential data more securely and quickly than traditional enterprise data warehouse systems.

Restraint:

High cost of autonomous data platforms

Companies' expectations are rising as a result of technological advancements. As a result, these businesses frequently update their cloud-based and customer-centric solutions to meet the requirements of gathering, analyzing, and sorting their customers' data. Furthermore, firms must make significant investments to adopt cloud-based and autonomous data platforms, which may limit demand for these platforms during the forecasted period.

Opportunity:

Growing awareness about the benefits of autonomous data platforms

The autonomous data platforms can encrypt data, track workloads, and monitor any entity that attempts to access the data. As a result, these platforms let businesses to use data without having to worry about regulatory or reputational damage from an improper environment. Furthermore, these systems provide exceptional flexibility, allowing businesses to grow or decrease capacity based on convenience and requirements.

Threat:

Lack of skilled professionals

Complex and costly integration, as well as restricted support and customization are some limitations and difficulties that can impede market expansion. Market limitations may be caused by things like a shortage of highly qualified workers and challenging analytical procedures. However, difficult analytical methods, a lack of competent and trained personnel, and issues connected with striking a balance between quality and safety are impeding market expansion.

COVID-19 Impact

The breakout of the COVID-19 pandemic has had an impact on the market for an autonomous data platform, and the sector's growth is projected to be driven post-pandemic. This is due to the increasing transmission rate of COVID-19 over the world, as well as the companies' use of work-from-home models to protect their employees from the deadly virus. As a result, many businesses have made significant investments in autonomous data platform solutions to streamline and boost productivity throughout their business activities. Furthermore, the rise in network dependency and network load during the pandemic time will boost the expansion of the autonomous data platform industry.

The cloud segment is expected to be the largest during the forecast period

The cloud segment is estimated to have a lucrative growth, due to the flexibility and cost-effectiveness of cloud-based solutions, users are more likely to prefer and adopt them. Cloud computing platforms provide for greater scalability, lower implementation costs, and continuous development. Implementing cloud-based solutions simplifies service delivery due to its virtual environment, which allows organisations to access information across interconnected devices at any time. Users can upload data to linked devices across a network rather than saving it locally on devices. These advantages provided by cloud adoption will boost segment growth.

The small and medium size enterprises segment is expected to have the highest CAGR during the forecast period

The small and medium size enterprises segment is anticipated to witness the fastest CAGR growth during the forecast period, due to the increase in investments in advanced techniques such as machine learning, expanding application of AI technology, and rising usage of digital payment systems. Because of increased volume, small and medium-sized organisations are expected to expand their demand for self-contained data structures. The autonomous data platform market will grow as machine learning and AI are used more frequently to improve decision-making.

Region with highest share:

North America is projected to hold the largest market share during the forecast period, because the region is home to the most developed economies, such as Canada and the United States, it is regarded as the most advanced region in terms of embracing cutting-edge technologies and cloud-based solutions. The increasing use of mobile phones and the internet in North America is driving significant industry growth. Furthermore, the increased use of smart phones and digital networking sites to engage with business partners and clients is helping the region's market expansion.

Region with highest CAGR:

Asia Pacific is projected to have the highest CAGR over the forecast period, owing to the increasing use of AI and machine learning to assist decision-making. Furthermore, the capacity of organisations to merge client data from multiple sources onto an uniform platform, decreasing hours of computing effort, is facilitating the demand for autonomous data platforms. Because of increasing expenditures in R&D activities to improve the capabilities of these platforms, the autonomous data platform business is anticipated to see new growth prospects. As a result, over the forecast period, the Asia Pacific area is likely to have strong momentum for autonomous database platforms.

Key players in the market

Some of the key players profiled in the Autonomous Data Platform Market include Oracle Corporation, Hewlett Packard Enterprise Development LP, Amazon Web Services, Inc., Teradata, IBM, Denodo Technologies, Alteryx, Inc., Gemini Data, Cloudera, Inc., Qubole, Inc., Paxata, Inc., Zaloni Inc., Ataccama Corporation, MapR Technologies, Inc. and Intellias Ltd.

Key Developments:

In September 2021, Alteryx formed a partnership with UiPath, a software company for robotic process automation. Through this partnership, the two companies jointly developed a new connector that allows Alteryx users to call out to UiPath bots and integrate UiPath's RPA capabilities into their workflows.

In January, 2021, Alteryx partnered with Snowflake, the Data Cloud company. Under this partnership, the analytics automation and data science capabilities of Alteryx would be integrated into Snowflake's platform. This integration would offer customers automated data pipelining, rapid data processing, and speed analytics outcomes at scale.

In December 2020, AWS came into a partnership with BlackBerry QNX, a subsidiary of BlackBerry. Through this partnership, the two companies would jointly create BlackBerry IVY, an Intelligent Vehicle Data Platform. Moreover, BlackBerry IVY can be defined as a scalable, cloud-connected software platform that enables automobile manufacturers to offer a constant and safe way to read vehicle sensor data, centralize it, and develop actionable insights from that data both locally in the vehicle and in the cloud.

In October 2020, IBM joined hands with AT&T, an American multinational conglomerate holding company. Through this collaboration, the two companies introduced Hybrid Cloud in order to help the companies better manage open hybrid cloud computing in a low-latency, private cellular network edge environment.

In 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.

In June 2019, Qubole introduced a self-service platform for data scientists and engineers to construct AI, machine learning, and analytics processes on their preferred public cloud.

In April 2019, MapR announced new MapR Data Platform innovations 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.

Components Covered:

  • Services
  • Platform

Deployments Covered:

  • Cloud
  • On-premises

Enterprises Covered:

  • Small and Medium Enterprise (SME)
  • Large Enterprise

End Users Covered:

  • Banking, Financial Services and Insurance (BFSI)
  • Healthcare and Life Sciences
  • Media and Telecommunication
  • Retail and Consumer Goods
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2020, 2021, 2022, 2025, and 2028
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Autonomous Data Platform Market, By Component

  • 5.1 Introduction
  • 5.2 Services
    • 5.2.1 Advisory
    • 5.2.2 Support and Maintenance
    • 5.2.3 Integration
  • 5.3 Platform

6 Global Autonomous Data Platform Market, By Deployment

  • 6.1 Introduction
  • 6.2 Cloud
  • 6.3 On-premises

7 Global Autonomous Data Platform Market, By Enterprise

  • 7.1 Introduction
  • 7.2 Small and Medium Enterprise (SME)
  • 7.3 Large Enterprise

8 Global Autonomous Data Platform Market, By End User

  • 8.1 Introduction
  • 8.2 Banking, Financial Services and Insurance (BFSI)
  • 8.3 Healthcare and Life Sciences
  • 8.4 Media and Telecommunication
  • 8.5 Retail and Consumer Goods
  • 8.6 Other End Users
    • 8.6.1 Energy & Utilities
    • 8.6.2 Travel & Hospitality
    • 8.6.3 Transportation & Logistics

9 Global Autonomous Data Platform Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Oracle Corporation
  • 11.2 Hewlett Packard Enterprise Development LP
  • 11.3 Amazon Web Services, Inc.
  • 11.4 Teradata
  • 11.5 IBM
  • 11.6 Denodo Technologies
  • 11.7 Alteryx, Inc.
  • 11.8 Gemini Data
  • 11.9 Cloudera, Inc.
  • 11.10 Qubole, Inc.
  • 11.11 Paxata, Inc.
  • 11.12 Zaloni Inc.
  • 11.13 Ataccama Corporation
  • 11.14 MapR Technologies, Inc.
  • 11.15 Intellias Ltd.

List of Tables

  • 1 Global Autonomous Data Platform Market Outlook, By Region (2020-2028) ($MN)
  • 2 Global Autonomous Data Platform Market Outlook, By Component (2020-2028) ($MN)
  • 3 Global Autonomous Data Platform Market Outlook, By Services (2020-2028) ($MN)
  • 4 Global Autonomous Data Platform Market Outlook, By Advisory (2020-2028) ($MN)
  • 5 Global Autonomous Data Platform Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • 6 Global Autonomous Data Platform Market Outlook, By Integration (2020-2028) ($MN)
  • 7 Global Autonomous Data Platform Market Outlook, By Platform (2020-2028) ($MN)
  • 8 Global Autonomous Data Platform Market Outlook, By Deployment (2020-2028) ($MN)
  • 9 Global Autonomous Data Platform Market Outlook, By Cloud (2020-2028) ($MN)
  • 10 Global Autonomous Data Platform Market Outlook, By On-premises (2020-2028) ($MN)
  • 11 Global Autonomous Data Platform Market Outlook, By Enterprise (2020-2028) ($MN)
  • 12 Global Autonomous Data Platform Market Outlook, By Small and Medium Enterprise (SME)(2020-2028) ($MN)
  • 13 Global Autonomous Data Platform Market Outlook, By Large Enterprise (2020-2028) ($MN)
  • 14 Global Autonomous Data Platform Market Outlook, By End User (2020-2028) ($MN)
  • 15 Global Autonomous Data Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
  • 16 Global Autonomous Data Platform Market Outlook, By Healthcare and Life Sciences (2020-2028) ($MN)
  • 17 Global Autonomous Data Platform Market Outlook, By Media and Telecommunication (2020-2028) ($MN)
  • 18 Global Autonomous Data Platform Market Outlook, By Retail and Consumer Goods (2020-2028) ($MN)
  • 19 Global Autonomous Data Platform Market Outlook, By Other End Users (2020-2028) ($MN)
  • 20 Global Autonomous Data Platform Market Outlook, By Energy & Utilities (2020-2028) ($MN)
  • 21 Global Autonomous Data Platform Market Outlook, By Travel & Hospitality (2020-2028) ($MN)
  • 22 Global Autonomous Data Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)
  • 23 North America Autonomous Data Platform Market Outlook, By Country (2020-2028) ($MN)
  • 24 North America Autonomous Data Platform Market Outlook, By Component (2020-2028) ($MN)
  • 25 North America Autonomous Data Platform Market Outlook, By Services (2020-2028) ($MN)
  • 26 North America Autonomous Data Platform Market Outlook, By Advisory (2020-2028) ($MN)
  • 27 North America Autonomous Data Platform Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • 28 North America Autonomous Data Platform Market Outlook, By Integration (2020-2028) ($MN)
  • 29 North America Autonomous Data Platform Market Outlook, By Platform (2020-2028) ($MN)
  • 30 North America Autonomous Data Platform Market Outlook, By Deployment (2020-2028) ($MN)
  • 31 North America Autonomous Data Platform Market Outlook, By Cloud (2020-2028) ($MN)
  • 32 North America Autonomous Data Platform Market Outlook, By On-premises (2020-2028) ($MN)
  • 33 North America Autonomous Data Platform Market Outlook, By Enterprise (2020-2028) ($MN)
  • 34 North America Autonomous Data Platform Market Outlook, By Small and Medium Enterprise (SME)(2020-2028) ($MN)
  • 35 North America Autonomous Data Platform Market Outlook, By Large Enterprise (2020-2028) ($MN)
  • 36 North America Autonomous Data Platform Market Outlook, By End User (2020-2028) ($MN)
  • 37 North America Autonomous Data Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
  • 38 North America Autonomous Data Platform Market Outlook, By Healthcare and Life Sciences (2020-2028) ($MN)
  • 39 North America Autonomous Data Platform Market Outlook, By Media and Telecommunication (2020-2028) ($MN)
  • 40 North America Autonomous Data Platform Market Outlook, By Retail and Consumer Goods (2020-2028) ($MN)
  • 41 North America Autonomous Data Platform Market Outlook, By Other End Users (2020-2028) ($MN)
  • 42 North America Autonomous Data Platform Market Outlook, By Energy & Utilities (2020-2028) ($MN)
  • 43 North America Autonomous Data Platform Market Outlook, By Travel & Hospitality (2020-2028) ($MN)
  • 44 North America Autonomous Data Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)
  • 45 Europe Autonomous Data Platform Market Outlook, By Country (2020-2028) ($MN)
  • 46 Europe Autonomous Data Platform Market Outlook, By Component (2020-2028) ($MN)
  • 47 Europe Autonomous Data Platform Market Outlook, By Services (2020-2028) ($MN)
  • 48 Europe Autonomous Data Platform Market Outlook, By Advisory (2020-2028) ($MN)
  • 49 Europe Autonomous Data Platform Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • 50 Europe Autonomous Data Platform Market Outlook, By Integration (2020-2028) ($MN)
  • 51 Europe Autonomous Data Platform Market Outlook, By Platform (2020-2028) ($MN)
  • 52 Europe Autonomous Data Platform Market Outlook, By Deployment (2020-2028) ($MN)
  • 53 Europe Autonomous Data Platform Market Outlook, By Cloud (2020-2028) ($MN)
  • 54 Europe Autonomous Data Platform Market Outlook, By On-premises (2020-2028) ($MN)
  • 55 Europe Autonomous Data Platform Market Outlook, By Enterprise (2020-2028) ($MN)
  • 56 Europe Autonomous Data Platform Market Outlook, By Small and Medium Enterprise (SME)(2020-2028) ($MN)
  • 57 Europe Autonomous Data Platform Market Outlook, By Large Enterprise (2020-2028) ($MN)
  • 58 Europe Autonomous Data Platform Market Outlook, By End User (2020-2028) ($MN)
  • 59 Europe Autonomous Data Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
  • 60 Europe Autonomous Data Platform Market Outlook, By Healthcare and Life Sciences (2020-2028) ($MN)
  • 61 Europe Autonomous Data Platform Market Outlook, By Media and Telecommunication (2020-2028) ($MN)
  • 62 Europe Autonomous Data Platform Market Outlook, By Retail and Consumer Goods (2020-2028) ($MN)
  • 63 Europe Autonomous Data Platform Market Outlook, By Other End Users (2020-2028) ($MN)
  • 64 Europe Autonomous Data Platform Market Outlook, By Energy & Utilities (2020-2028) ($MN)
  • 65 Europe Autonomous Data Platform Market Outlook, By Travel & Hospitality (2020-2028) ($MN)
  • 66 Europe Autonomous Data Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)
  • 67 Asia Pacific Autonomous Data Platform Market Outlook, By Country (2020-2028) ($MN)
  • 68 Asia Pacific Autonomous Data Platform Market Outlook, By Component (2020-2028) ($MN)
  • 69 Asia Pacific Autonomous Data Platform Market Outlook, By Services (2020-2028) ($MN)
  • 70 Asia Pacific Autonomous Data Platform Market Outlook, By Advisory (2020-2028) ($MN)
  • 71 Asia Pacific Autonomous Data Platform Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • 72 Asia Pacific Autonomous Data Platform Market Outlook, By Integration (2020-2028) ($MN)
  • 73 Asia Pacific Autonomous Data Platform Market Outlook, By Platform (2020-2028) ($MN)
  • 74 Asia Pacific Autonomous Data Platform Market Outlook, By Deployment (2020-2028) ($MN)
  • 75 Asia Pacific Autonomous Data Platform Market Outlook, By Cloud (2020-2028) ($MN)
  • 76 Asia Pacific Autonomous Data Platform Market Outlook, By On-premises (2020-2028) ($MN)
  • 77 Asia Pacific Autonomous Data Platform Market Outlook, By Enterprise (2020-2028) ($MN)
  • 78 Asia Pacific Autonomous Data Platform Market Outlook, By Small and Medium Enterprise (SME)(2020-2028) ($MN)
  • 79 Asia Pacific Autonomous Data Platform Market Outlook, By Large Enterprise (2020-2028) ($MN)
  • 80 Asia Pacific Autonomous Data Platform Market Outlook, By End User (2020-2028) ($MN)
  • 81 Asia Pacific Autonomous Data Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
  • 82 Asia Pacific Autonomous Data Platform Market Outlook, By Healthcare and Life Sciences (2020-2028) ($MN)
  • 83 Asia Pacific Autonomous Data Platform Market Outlook, By Media and Telecommunication (2020-2028) ($MN)
  • 84 Asia Pacific Autonomous Data Platform Market Outlook, By Retail and Consumer Goods (2020-2028) ($MN)
  • 85 Asia Pacific Autonomous Data Platform Market Outlook, By Other End Users (2020-2028) ($MN)
  • 86 Asia Pacific Autonomous Data Platform Market Outlook, By Energy & Utilities (2020-2028) ($MN)
  • 87 Asia Pacific Autonomous Data Platform Market Outlook, By Travel & Hospitality (2020-2028) ($MN)
  • 88 Asia Pacific Autonomous Data Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)
  • 89 South America Autonomous Data Platform Market Outlook, By Country (2020-2028) ($MN)
  • 90 South America Autonomous Data Platform Market Outlook, By Component (2020-2028) ($MN)
  • 91 South America Autonomous Data Platform Market Outlook, By Services (2020-2028) ($MN)
  • 92 South America Autonomous Data Platform Market Outlook, By Advisory (2020-2028) ($MN)
  • 93 South America Autonomous Data Platform Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • 94 South America Autonomous Data Platform Market Outlook, By Integration (2020-2028) ($MN)
  • 95 South America Autonomous Data Platform Market Outlook, By Platform (2020-2028) ($MN)
  • 96 South America Autonomous Data Platform Market Outlook, By Deployment (2020-2028) ($MN)
  • 97 South America Autonomous Data Platform Market Outlook, By Cloud (2020-2028) ($MN)
  • 98 South America Autonomous Data Platform Market Outlook, By On-premises (2020-2028) ($MN)
  • 99 South America Autonomous Data Platform Market Outlook, By Enterprise (2020-2028) ($MN)
  • 100 South America Autonomous Data Platform Market Outlook, By Small and Medium Enterprise (SME)(2020-2028) ($MN)
  • 101 South America Autonomous Data Platform Market Outlook, By Large Enterprise (2020-2028) ($MN)
  • 102 South America Autonomous Data Platform Market Outlook, By End User (2020-2028) ($MN)
  • 103 South America Autonomous Data Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
  • 104 South America Autonomous Data Platform Market Outlook, By Healthcare and Life Sciences (2020-2028) ($MN)
  • 105 South America Autonomous Data Platform Market Outlook, By Media and Telecommunication (2020-2028) ($MN)
  • 106 South America Autonomous Data Platform Market Outlook, By Retail and Consumer Goods (2020-2028) ($MN)
  • 107 South America Autonomous Data Platform Market Outlook, By Other End Users (2020-2028) ($MN)
  • 108 South America Autonomous Data Platform Market Outlook, By Energy & Utilities (2020-2028) ($MN)
  • 109 South America Autonomous Data Platform Market Outlook, By Travel & Hospitality (2020-2028) ($MN)
  • 110 South America Autonomous Data Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)
  • 111 Middle East & Africa Autonomous Data Platform Market Outlook, By Country (2020-2028) ($MN)
  • 112 Middle East & Africa Autonomous Data Platform Market Outlook, By Component (2020-2028) ($MN)
  • 113 Middle East & Africa Autonomous Data Platform Market Outlook, By Services (2020-2028) ($MN)
  • 114 Middle East & Africa Autonomous Data Platform Market Outlook, By Advisory (2020-2028) ($MN)
  • 115 Middle East & Africa Autonomous Data Platform Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • 116 Middle East & Africa Autonomous Data Platform Market Outlook, By Integration (2020-2028) ($MN)
  • 117 Middle East & Africa Autonomous Data Platform Market Outlook, By Platform (2020-2028) ($MN)
  • 118 Middle East & Africa Autonomous Data Platform Market Outlook, By Deployment (2020-2028) ($MN)
  • 119 Middle East & Africa Autonomous Data Platform Market Outlook, By Cloud (2020-2028) ($MN)
  • 120 Middle East & Africa Autonomous Data Platform Market Outlook, By On-premises (2020-2028) ($MN)
  • 121 Middle East & Africa Autonomous Data Platform Market Outlook, By Enterprise (2020-2028) ($MN)
  • 122 Middle East & Africa Autonomous Data Platform Market Outlook, By Small and Medium Enterprise (SME)(2020-2028) ($MN)
  • 123 Middle East & Africa Autonomous Data Platform Market Outlook, By Large Enterprise (2020-2028) ($MN)
  • 124 Middle East & Africa Autonomous Data Platform Market Outlook, By End User (2020-2028) ($MN)
  • 125 Middle East & Africa Autonomous Data Platform Market Outlook, By Banking, Financial Services and Insurance (BFSI) (2020-2028) ($MN)
  • 126 Middle East & Africa Autonomous Data Platform Market Outlook, By Healthcare and Life Sciences (2020-2028) ($MN)
  • 127 Middle East & Africa Autonomous Data Platform Market Outlook, By Media and Telecommunication (2020-2028) ($MN)
  • 128 Middle East & Africa Autonomous Data Platform Market Outlook, By Retail and Consumer Goods (2020-2028) ($MN)
  • 129 Middle East & Africa Autonomous Data Platform Market Outlook, By Other End Users (2020-2028) ($MN)
  • 130 Middle East & Africa Autonomous Data Platform Market Outlook, By Energy & Utilities (2020-2028) ($MN)
  • 131 Middle East & Africa Autonomous Data Platform Market Outlook, By Travel & Hospitality (2020-2028) ($MN)
  • 132 Middle East & Africa Autonomous Data Platform Market Outlook, By Transportation & Logistics (2020-2028) ($MN)