查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1250707

全球數據貨幣化市場：到 2028 年的預測 - 按類型、組件、數據類型、業務功能、部署類型、組織規模、方法論、最終用戶和地區分析

Data Monetization Market Forecasts to 2028 - Global Analysis By Type, By Component, By Data Type, By Business Function, By Deployment Type, By Organization Size, By Method, By End User and By 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 的數據，2022 年全球數據貨幣化市場規模將達到 29 億美元，預計到 2028 年將達到 93.3 億美元，預測期內以 21.5% 的複合年增長率增長。

數據貨幣化是一種技術，用於將大量非結構化和未使用的企業數據轉化為有洞察力的知識，以換取金錢和服務。通過投資分析平台，根據需求將非結構化數據轉化為有用的見解，企業可以降低業務流程成本並增加收入流。

據Phillips稱，截至 2022 年 2 月，在新加坡接受調查的醫療保健領導者中有 92% 表示他們已經或正在其醫療保健組織中實施預測分析。

市場動態：

促進者

越來越多地採用數據驅動的決策

組織使用數據來做出重要決策。在使用商業智能 (BI) 軟件和工具之前，數據分析決策是基於直覺、直覺和意見的傳統方法。然而，組織開始意識到這些方法可以提高盈利能力並用於更好的戰略決策。例如，根據美國中央銀行的一項研究，2005 年至 2010 年間，美國製造業中數據驅動的決策制定增加了兩倍。

抑製劑

缺乏組織能力和文化障礙

大數據利用的主要障礙是組織能力和文化。數據貨幣化工具的使用預計會受到障礙的阻礙，例如缺乏適當的角色和職責、低效的組織流程、缺乏管理重點和支持，以及缺乏程序和質量衡量。數據貨幣化需要特定的程序、工具和能力，但最重要的是，需要一種促進創新產品開發的文化。數據貨幣化是關於開發新的業務線，擁有清晰的業務戰略、有效的業務部門領導者和合格的員工至關重要。

機會

將 AI 引入數據處理的運動正在蓄勢待發

組織被迫採用人工智能、物聯網、機器學習和深度學習等新技術，因為它們會生成大量數據，並且需要實時評估這些數據。組織正在專注於部署 BI 技術，因為它可以非常有助於收集和分析大量數據。數據貨幣化解決方案可幫助您處理大量數據並從手頭的信息中獲得有用的見解。例如，許多公司使用 BI 工具，利用豐富的數據分析自己的產品、服務和客戶行為模式。這些工具還用於分析大數據集並得出可用於開發市場機會和企業戰略的分析見解。

威脅

複雜的數據結構

數據質量是數據貨幣化的關鍵考慮因素之一，它在各個行業無處不在，並帶來新的商機。準確的數據使組織能夠做出正確的決定。特定行業的數據共享和數據產品與現有系統的集成會降低數據質量。數據質量差會導致虛假事實和差異。因此，公司做出明智決策的能力直接受到數據質量的影響。沒有質量，信息效率低下，並可能導致不可預測的結果。因此，預計組織獲取的數據質量將難以利用數據貨幣化解決方案並限制數據貨幣化供應商的發展。

COVID-19 的影響

COVID-19 流行病導致開發新的解決方案，為客戶提供預測性和規範性分析，簡化業務流程以做出節省成本的決策。客戶從這種數據貨幣化方法中獲得最大價值，產品團隊可以創建和部署與其他軟件無縫集成的可操作分析應用程序。通過使用數據貨幣化技術和服務，企業可以獲得可以增加數據價值的秘密信息。通過了解客戶的購買行為和模式，這些工具和服務可以滿足消費者的獨特需求並改善整體客戶體驗。

工具部分預計將在預測期內成為最大的部分

預計工具部分將在預測期內佔據最大的市場份額。業務應用程序採用數據貨幣化技術來改進功能，從業務數據中提取見解，並使企業能夠做出明智的業務決策。數據貨幣化平台的既定功能支持跨技術集成結構化和非結構化數據。此外，數據貨幣化解決方案使數據貨幣化提供商能夠通過提高滿足客戶特定要求的能力來增加市場份額並產生更多利潤。

客戶數據部分預計在預測期內見證最高的複合年增長率

客戶數據部分在預測期內顯示出最高的增長率。這是因為重要的消費者數據有助於公司製定戰略。客戶關係管理 (CRM) 系統允許企業從廣告、調查、社交媒體和網站收集客戶數據。借助客戶數據，公司可以重塑自我並為其核心業務創造新的收入來源。了解目標市場的購買模式並分析產品設計和定價決策以便為客戶定制產品和服務也很有用。例如，Facebook 分析用戶數據並將其出售給外部公司，以便它可以展示為這些公司量身定制的廣告。

市場佔有率最高的地區

由於日本、中國和澳大利亞等國家人口眾多，亞太地區預計在預測期內將佔最大份額。因此，這些國家的企業需要快速實現數據貨幣化，以管理海量數據。此外，推動市場增長的主要因素是物聯網、移動性、人工智能、雲、頂級服務等數字服務的利用率不斷提高，以及對該地區技術進步的投資不斷增加。然而，由於眾多中小微企業和大型企業的存在、業務運營的數字化程度不斷提高以及產生的數據量不斷增加，中國是該地區最賺錢的地區。

複合年增長率最高的地區：

由於物聯網和雲計算等尖端技術的利用率不斷提高，亞太地區預計在整個預測期內將獲得顯著的增長機會。在亞太地區，公司數量正在增加。例如，新加坡有超過20萬家公司。這是亞太地區增長率最高的主要原因之一。然而，在 BFSI、零售、醫療保健和生命科學行業的垂直整合中採用數據貨幣化工具將導致大數據和業務分析解決方案的出現，這些解決方案可以提高業務績效、檢測欺詐並在全球經濟中保持競爭力。可能會加速通過大量投資

重大發展

2022 年 9 月，SAS 宣布其分析平台 Viya 現已在 Microsoft Azure Marketplace 上架。Microsoft Azure 上的 SAS Viya 的全部功能將為世界各地的客戶提供訪問數據探索、機器學習和模型部署的分析。該工具提供多種語言版本，並包含一個應用內學習中心以支持即時入門。Microsoft Azure 上的 SAS Viya 還將提供對完整 Viya 包的訪問，包括 SAS Visual Analytics、SAS Visual Statistics、SAS Visual Data Mining、Machine Learning 和 SAS Model Manager。

2022 年 7 月，Google將推出新的維度和指標，以查看跳出率、額外的 UTM 參數值和跨各種表面的轉化率，包括探索、細分、受眾、報告和 Google Analytics Data API 現在可以

2022 年 6 月，英國民航局 (CAA) 將部署 Emu Analytics 的數字孿生解決方案 Flo.W，以監控英國領空的使用情況並提高安全性、效率和效率。針對未來做出明智的、數據驅動的決策所有空域用戶，將他們考慮在內。

2022 年 1 月，Optiva, Inc. 和 Google Cloud 建立了多年戰略合作夥伴關係。該合作夥伴關係旨在幫助運營商和服務提供商更好地擁抱數字化轉型。

2021 年 8 月，Adastra 和 PaymentComponents 宣布即將建立合作夥伴關係，以在美國和加拿大提供先進的開放式銀行和支付解決方案。Adastra 和 PaymentComponents 的綜合實力將為客戶提供可以有效推向市場的獨特解決方案，從而增強後者作為該地區綜合金融科技解決方案提供商的地位。

本報告提供的內容

  • 區域和國家級細分市場份額評估
  • 對新進入者的戰略建議
  • 涵蓋 2020、2021、2022、2025 和 2028 年的市場數據
  • 市場驅動因素（市場趨勢、制約因素、機會、威脅、挑戰、投資機會/建議等）
  • 基於市場估計的關鍵業務領域的戰略建議
  • 競爭格局和趨勢
  • 公司概況，包括詳細戰略、財務狀況和近期發展
  • 供應鏈趨勢反映了最新的技術進步。

提供免費定制

購買此報告的客戶將免費獲得以下定制之一。

  • 公司簡介
    • 其他市場參與者的綜合分析（最多 3 個）
    • 關鍵參與者的 SWOT 分析（最多 3 個參與者）
  • 區域部分
    • 應客戶要求提供主要國家/地區的市場估計、預測和 CAGR（注：不包括可行性檢查。）
  • 競爭標桿

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

目錄

第一章內容提要

第二章前言

  • 概述
  • 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
  • 研究來源
    • 主要研究來源
    • 二手研究資源
    • 假設

第三章市場趨勢分析

  • 促進者
  • 抑製劑
  • 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
  • 買方議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5 全球數據貨幣化市場，按類型

  • 直接數據貨幣化
  • 間接數據貨幣化

6. 全球數據貨幣化市場，按組件

  • 服務
    • 諮詢
    • 實施與整合
    • 支持和維護
  • 工具
  • 軟件

7. 全球數據貨幣化市場，按數據類型

  • 供應商資料
  • 產品數據
  • 客戶資料
  • 財務數據

8 全球數據貨幣化市場，按業務功能

  • 金融
  • 供應鏈管理
  • 銷售與市場營銷
  • 銷售量
  • 其他業務功能

9 全球數據貨幣化市場，按部署類型

  • 本地
  • 雲

10 全球數據貨幣化市場，按組織規模

  • 中小企業
  • 大公司

11 全球數據貨幣化市場：按方法

  • 即服務即服務
  • 嵌入式分析
  • 數據即服務
  • 服務即服務

12. 全球數據貨幣化市場，按最終用戶分類

  • 溝通
  • 銀行、金融服務、保險
  • 信息技術
  • 消費品和零售
  • 製造業
  • 衛生保健
  • 運輸
  • 媒體和娛樂
  • 能源和公用事業
  • 其他最終用戶

13. 全球數據貨幣化市場，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
    • 歐洲其他地區
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳大利亞
    • 新西蘭
    • 韓國
    • 亞太其他地區
  • 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

第 14 章主要進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第十五章公司簡介

  • Accenture plc
  • ALC
  • Monetize Solutions, Inc.
  • Adastra Corporation
  • Optiva, Inc.（Redknee Solutions Inc.）
  • Reltio
  • Cisco Systems, Inc.
  • SAP SE
  • Mahindra ComViva
  • SAS Institute Inc.
  • VIAVI Solutions Inc.
  • Emu Analytics Ltd.
  • Thales Group
  • Google LLC（Alphabet Inc.）
  • IBM Corporation
  • Infosys Limited
  • Ness Technologies Inc
  • NetScout Systems Inc.
  • Openwave Mobility Inc.（ENEA）
  • Dawex Systems SAS
Product Code: SMRC22584

According to Stratistics MRC, the Global Data Monetization Market is accounted for $2.90 billion in 2022 and is expected to reach $9.33 billion by 2028 growing at a CAGR of 21.5% during the forecast period. Data monetization is the method used to transform a vast volume of unstructured, unused company data into insightful knowledge that can then be exchanged for money or services. By investing in analytics platforms that transform unstructured data into useful insights based on requirements, businesses can lower the cost of their business processes and enhance income streams.

According to Philips, as of February 2022, 92% of healthcare leaders surveyed in Singapore declared they had already implemented or had been in the process of adopting predictive analytics in their healthcare organizations.

Market Dynamics:

Driver:

Growth in the adoption of data-driven decision-making

Data is being used by organizations to make important decisions. Prior to the use of Business Intelligence (BI) software and tools, data analysis decisions were based on conventional methods like intuitions, hunches, or opinions. However, organizations have begun to realize that these methods improve profitability and can be used to make better strategic decisions. Several businesses are adopting BI; for instance, data-driven decision-making among US manufacturers increased threefold between 2005 and 2010, according to U.S. Central Bureau Surveys.

Restraint:

Lack of 0rganizational capabilities and cultural barriers

The main hindrances to big data exploitation are organizational capabilities and culture. The use of data monetization tools is predicted to be hampered by obstacles such as a lack of adequate roles and responsibilities, ineffective organizational processes, a lack of management focus and support, and a lack of procedures and quality measurements. Data monetization necessitates a certain set of procedures, tools, and abilities, but most significantly, it needs a culture that is conducive to the development of novel products. As data monetization is all about developing a new line of business, having a clear business strategy, an effective business unit leader, and a capable staff are crucial.

Opportunity:

Rising adoption of AI for data processing

Organizations have been forced to adopt new technologies like AI, IoT, machine learning, and deep learning due to the production of enormous amounts of data and the requirement to evaluate this data in real-time. Since BI technologies are extremely helpful in gathering and analyzing enormous volumes of data, organizations are concentrating on adopting them. Solutions for data monetization can process huge quantities of data and assist in gaining useful insights from the information at hand. For instance, many companies utilize BI tools to analyze their products, services, and customer behavior patterns using a wealth of data. These tools are also used to analyze big data sets and derive analytical insights that can be used to market opportunities and develop company strategies.

Threat:

Increase in complexities in data structures

Data quality is one of the key considerations for monetizing data, which is becoming more widespread across industries and offering new business opportunities. Organizations can determine this correctly owing to precise data. Data quality may be lowered as a result of industry-specific data sharing and the integration of data products into existing systems. False facts and inconsistencies could be the result of poor data quality. The ability of companies to make wise decisions is therefore directly impacted by adequate data quality. Without quality, information is inefficient and can have unexpected consequences. As a result, it is anticipated that the quality of the data obtained by organizations will make it difficult to use data monetization solutions, which will restrict the development of data monetization vendors.

Covid-19 Impact:

Owing to the COVID-19 epidemic, new solutions have evolved that provide their customers with predictive and prescriptive analysis, allowing them to make decisions about cost reduction by simplifying their business processes. Customers receive the most value from this method of data monetization, which also enables product teams to create and deploy actionable analytics apps that can be seamlessly integrated with other software. Enterprises can extract secret information that can add value to the company's data with the use of technologies and services for data monetization. By comprehending customers' purchasing behaviors and patterns, these tools and services also meet the consumers' inherent demands, improving the entire customer experience.

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

During the forecast period, the tools segment is anticipated to hold the largest market share as business applications employ data monetization techniques to improve their functionality and extract insights from the business data, allowing businesses to make wise business decisions. The integration of structured and unstructured data across technologies is made possible by the established features of the data monetization platform. Moreover, the data monetization solution gives data monetization providers the ability to grow their market shares and make more money by improving their capacity to meet the unique requirements of their customers.

The customer data segment is expected to have the highest CAGR during the forecast period

Over the predicted period, the customer data segment commanded the highest growth rate, as crucial consumer data assists businesses in developing their company strategy. With the aid of customer relationship management (CRM) systems, businesses gather client data from advertisements, surveys, social media, and websites. Because of client data, businesses can reinvent themselves and create new revenue streams for their core business. In order to tailor their products and services for their clients, businesses also benefit from understanding the buying patterns of their target market and analyzing their judgments about product design and pricing. For instance, Facebook analyzes user data and sells it to outside companies so that they may display tailored advertisements.

Region with largest share:

Due to the enormous populations of nations like Japan, China, and Australia, the Asia-Pacific region is predicted to have the largest share during the projected period. Hence, in order to manage a vast volume of data, enterprises in these nations are required to implement data monetization at a rapid rate. Moreover, the major factors driving market growth are the expanding usage of digital services like IoT, mobility, AI, cloud, and over-the-top services, as well as the rising investments in technological advancements in the region. However, China generates the most revenue in the region, which is due to the existence of several MSMEs and large companies, the ongoing digitalization of business operations, and the rise in the amount of data generated.

Region with highest CAGR:

Due to the increased usage of cutting-edge technologies like IoT and cloud computing, Asia Pacific is anticipated to experience significant growth opportunities throughout the forecast period. The number of businesses is rising in the Asia-Pacific region. For instance, Singapore is dedicated for more than 200,000 businesses. This is one of the primary causes behind Asia-Pacific's highest growth rate. However, the adoption of data monetization tools in the BFSI, retail, healthcare, and life sciences industry verticals would be accelerated by significant investments in big data and business analytics solutions that would enhance business performance, expose fraud, and maintain a competitive edge in the global economy.

Key Players in the market

Some of the key players in Data Monetization market include Accenture plc, ALC, Monetize Solutions, Inc., Adastra Corporation, Optiva, Inc. (Redknee Solutions Inc.), Reltio, Cisco Systems, Inc., SAP SE, Mahindra ComViva , SAS Institute Inc., VIAVI Solutions Inc., Emu Analytics Ltd., Thales Group, Google LLC (Alphabet Inc.), IBM Corporation, Infosys Limited, Ness Technologies Inc, NetScout Systems Inc., Openwave Mobility Inc. (ENEA) and Dawex Systems SAS.

Key Developments:

In September 2022, SAS announced that its Viya analytics platform is available in the Microsoft Azure Marketplace. All features of SAS Viya on Microsoft Azure would equip customers globally with access to data exploration, machine learning, and model deployment analytics. The tool is available in many languages and includes an in-app learning center to support immediate onboarding. With SAS Viya on Microsoft Azure, users would also have access to the complete Viya package, including SAS Visual Analytics, SAS Visual Statistics, SAS Visual Data Mining, Machine Learning, and SAS Model Manager.

In July 2022, Google launched new dimensions and metrics, enabling customers to see bounce rate, additional UTM parameter values, and conversion rate across various surfaces, including explorations, segments, audiences, reports, and the Google Analytics Data API.

In June 2022, The UK Civil Aviation Authority (CAA) aligned Emu Analytics' digital twin solution, Flo. W, to monitor how UK airspace is utilized and make informed, data-led decisions on its future, accounting for safety, efficiency, and all airspace users.

In January 2022, Optiva, Inc. and Google Cloud entered into a multi-year strategic partnership. The partnership was aimed at aiding telecom operators and service providers to better adopt digital transformation.

In August 2021, Adastra and PaymentComponents announced a partnership through which they plan to offer advanced open banking and payment solutions in the US and Canada. The combined strengths of Adastra and PaymentComponents can offer their customers exclusive solutions that they can take to market effectively and boost the latter's position as a comprehensive fintech solutions provider in the region.

Types Covered:

  • Direct Data Monetization
  • Indirect Data Monetization

Components Covered:

  • Services
  • Tools
  • Software

Data Types Covered:

  • Supplier Data
  • Product Data
  • Customer Data
  • Financial Data

Business Functions Covered:

  • Finance
  • Supply Chain Management
  • Sales and Marketing
  • Operations
  • Other Business Functions

Deployment Types Covered:

  • On Premises
  • Cloud

Organization Sizes Covered:

  • Small and Medium Sized Enterprises
  • Large Enterprises

Methods Covered:

  • Insight as a Service (IaaS)
  • Embedded Analytics
  • Data as a Service (DaaS)
  • Analytics Enabled Platform as a Service (AaaS)

End Users Covered:

  • Telecommunication
  • Banking, Financial Services and Insurance
  • Information Technology
  • Consumer Goods and Retail
  • Manufacturing
  • Healthcare
  • Transportation and Logistics
  • Media and Entertainment
  • Energy and Utilities
  • 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 Data Monetization Market, By Type

  • 5.1 Introduction
  • 5.2 Direct Data Monetization
  • 5.3 Indirect Data Monetization

6 Global Data Monetization Market, By Component

  • 6.1 Introduction
  • 6.2 Services
    • 6.2.1 Consulting
    • 6.2.2 Implementation and Integration
    • 6.2.3 Support and Maintenance
  • 6.3 Tools
  • 6.4 Software

7 Global Data Monetization Market, By Data Type

  • 7.1 Introduction
  • 7.2 Supplier Data
  • 7.3 Product Data
  • 7.4 Customer Data
  • 7.5 Financial Data

8 Global Data Monetization Market, By Business Function

  • 8.1 Introduction
  • 8.2 Finance
  • 8.3 Supply Chain Management
  • 8.4 Sales and Marketing
  • 8.5 Operations
  • 8.6 Other Business Functions

9 Global Data Monetization Market, By Deployment Type

  • 9.1 Introduction
  • 9.2 On Premises
  • 9.3 Cloud

10 Global Data Monetization Market, By Organization Size

  • 10.1 Introduction
  • 10.2 Small and Medium Sized Enterprises
  • 10.3 Large Enterprises

11 Global Data Monetization Market, By Method

  • 11.1 Introduction
  • 11.2 Insight as a Service (IaaS)
  • 11.3 Embedded Analytics
  • 11.4 Data as a Service (DaaS)
  • 11.5 Analytics Enabled Platform as a Service (AaaS)

12 Global Data Monetization Market, By End User

  • 12.1 Introduction
  • 12.2 Telecommunication
  • 12.3 Banking, Financial Services and Insurance
  • 12.4 Information Technology
  • 12.5 Consumer Goods and Retail
  • 12.6 Manufacturing
  • 12.7 Healthcare
  • 12.8 Transportation and Logistics
  • 12.9 Media and Entertainment
  • 12.10 Enegy and Utilities
  • 12.11 Other End Users

13 Global Data Monetization Market, By Geography

  • 13.1 Introduction
  • 13.2 North America
    • 13.2.1 US
    • 13.2.2 Canada
    • 13.2.3 Mexico
  • 13.3 Europe
    • 13.3.1 Germany
    • 13.3.2 UK
    • 13.3.3 Italy
    • 13.3.4 France
    • 13.3.5 Spain
    • 13.3.6 Rest of Europe
  • 13.4 Asia Pacific
    • 13.4.1 Japan
    • 13.4.2 China
    • 13.4.3 India
    • 13.4.4 Australia
    • 13.4.5 New Zealand
    • 13.4.6 South Korea
    • 13.4.7 Rest of Asia Pacific
  • 13.5 South America
    • 13.5.1 Argentina
    • 13.5.2 Brazil
    • 13.5.3 Chile
    • 13.5.4 Rest of South America
  • 13.6 Middle East & Africa
    • 13.6.1 Saudi Arabia
    • 13.6.2 UAE
    • 13.6.3 Qatar
    • 13.6.4 South Africa
    • 13.6.5 Rest of Middle East & Africa

14 Key Developments

  • 14.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 14.2 Acquisitions & Mergers
  • 14.3 New Product Launch
  • 14.4 Expansions
  • 14.5 Other Key Strategies

15 Company Profiling

  • 15.1 Accenture plc
  • 15.2 ALC
  • 15.3 Monetize Solutions, Inc.
  • 15.4 Adastra Corporation
  • 15.5 Optiva, Inc. (Redknee Solutions Inc.)
  • 15.6 Reltio
  • 15.7 Cisco Systems, Inc.
  • 15.8 SAP SE
  • 15.9 Mahindra ComViva
  • 15.10 SAS Institute Inc.
  • 15.11 VIAVI Solutions Inc.
  • 15.12 Emu Analytics Ltd.
  • 15.13 Thales Group
  • 15.14 Google LLC (Alphabet Inc.)
  • 15.15 IBM Corporation
  • 15.16 Infosys Limited
  • 15.17 Ness Technologies Inc
  • 15.18 NetScout Systems Inc.
  • 15.19 Openwave Mobility Inc. (ENEA)
  • 15.20 Dawex Systems SAS

List of Tables

  • Table 1 Global Data Monetization Market Outlook, By Region (2020-2028) ($MN)
  • Table 2 Global Data Monetization Market Outlook, By Type (2020-2028) ($MN)
  • Table 3 Global Data Monetization Market Outlook, By Direct Data Monetization (2020-2028) ($MN)
  • Table 4 Global Data Monetization Market Outlook, By Indirect Data Monetization (2020-2028) ($MN)
  • Table 5 Global Data Monetization Market Outlook, By Component (2020-2028) ($MN)
  • Table 6 Global Data Monetization Market Outlook, By Services (2020-2028) ($MN)
  • Table 7 Global Data Monetization Market Outlook, By Consulting (2020-2028) ($MN)
  • Table 8 Global Data Monetization Market Outlook, By Implementation and Integration (2020-2028) ($MN)
  • Table 9 Global Data Monetization Market Outlook, By Support and Maintenance (2020-2028) ($MN)
  • Table 10 Global Data Monetization Market Outlook, By Tools (2020-2028) ($MN)
  • Table 11 Global Data Monetization Market Outlook, By Software (2020-2028) ($MN)
  • Table 12 Global Data Monetization Market Outlook, By Data Type (2020-2028) ($MN)
  • Table 13 Global Data Monetization Market Outlook, By Supplier Data (2020-2028) ($MN)
  • Table 14 Global Data Monetization Market Outlook, By Product Data (2020-2028) ($MN)
  • Table 15 Global Data Monetization Market Outlook, By Customer Data (2020-2028) ($MN)
  • Table 16 Global Data Monetization Market Outlook, By Financial Data (2020-2028) ($MN)
  • Table 17 Global Data Monetization Market Outlook, By Business Function (2020-2028) ($MN)
  • Table 18 Global Data Monetization Market Outlook, By Finance (2020-2028) ($MN)
  • Table 19 Global Data Monetization Market Outlook, By Supply Chain Management (2020-2028) ($MN)
  • Table 20 Global Data Monetization Market Outlook, By Sales and Marketing (2020-2028) ($MN)
  • Table 21 Global Data Monetization Market Outlook, By Operations (2020-2028) ($MN)
  • Table 22 Global Data Monetization Market Outlook, By Other Business Functions (2020-2028) ($MN)
  • Table 23 Global Data Monetization Market Outlook, By Deployment Type (2020-2028) ($MN)
  • Table 24 Global Data Monetization Market Outlook, By On Premises (2020-2028) ($MN)
  • Table 25 Global Data Monetization Market Outlook, By Cloud (2020-2028) ($MN)
  • Table 26 Global Data Monetization Market Outlook, By Organization Size (2020-2028) ($MN)
  • Table 27 Global Data Monetization Market Outlook, By Small and Medium Sized Enterprises (2020-2028) ($MN)
  • Table 28 Global Data Monetization Market Outlook, By Large Enterprises (2020-2028) ($MN)
  • Table 29 Global Data Monetization Market Outlook, By Method (2020-2028) ($MN)
  • Table 30 Global Data Monetization Market Outlook, By Insight as a Service (IaaS) (2020-2028) ($MN)
  • Table 31 Global Data Monetization Market Outlook, By Embedded Analytics (2020-2028) ($MN)
  • Table 32 Global Data Monetization Market Outlook, By Data as a Service (DaaS) (2020-2028) ($MN)
  • Table 33 Global Data Monetization Market Outlook, By Analytics Enabled Platform as a Service (AaaS) (2020-2028) ($MN)
  • Table 34 Global Data Monetization Market Outlook, By End User (2020-2028) ($MN)
  • Table 35 Global Data Monetization Market Outlook, By Telecommunication (2020-2028) ($MN)
  • Table 36 Global Data Monetization Market Outlook, By Banking, Financial Services and Insurance (2020-2028) ($MN)
  • Table 37 Global Data Monetization Market Outlook, By Information Technology (2020-2028) ($MN)
  • Table 38 Global Data Monetization Market Outlook, By Consumer Goods and Retail (2020-2028) ($MN)
  • Table 39 Global Data Monetization Market Outlook, By Manufacturing (2020-2028) ($MN)
  • Table 40 Global Data Monetization Market Outlook, By Healthcare (2020-2028) ($MN)
  • Table 41 Global Data Monetization Market Outlook, By Transportation and Logistics (2020-2028) ($MN)
  • Table 42 Global Data Monetization Market Outlook, By Media and Entertainment (2020-2028) ($MN)
  • Table 43 Global Data Monetization Market Outlook, By Enegy and Utilities (2020-2028) ($MN)
  • Table 44 Global Data Monetization Market Outlook, By Other End Users (2020-2028) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.