查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1250707

全球数据货币化市场：到 2028 年的预测 - 按类型、组件、数据类型、业务功能、部署类型、组织规模、方法论、最终用户和地区分析

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个工作天内

价格

根据 Stratistics MRC 的数据，2022 年全球数据货币化市场规模将达到 29 亿美元，预计到 2028 年将达到 93.3 亿美元，预测期内以 21.5% 的复合年增长率增长。

数据货币化是一种技术，用于将大量非结构化和未使用的企业数据转化为有洞察力的知识，以换取金钱和服务。通过投资分析平台，根据需求将非结构化数据转化为有用的见解，企业可以降低业务流程成本并增加收入流。

据Phillips称，截至 2022 年 2 月，在新加坡接受调查的医疗保健领导者中有 92% 表示他们已经或正在其医疗保健组织中实施预测分析。

市场动态：

促进者

越来越多地采用数据驱动的决策

组织使用数据来做出重要决策。在使用商业智能 (BI) 软件和工具之前，数据分析决策是基于直觉、直觉和意见的传统方法。然而，组织开始意识到这些方法可以提高盈利能力并用于更好的战略决策。例如，根据美国中央银行的一项研究，2005 年至 2010 年间，美国製造业中数据驱动的决策制定增加了两倍。

抑製剂

缺乏组织能力和文化障碍

大数据利用的主要障碍是组织能力和文化。数据货币化工具的使用预计会受到障碍的阻碍，例如缺乏适当的角色和职责、低效的组织流程、缺乏管理重点和支持，以及缺乏程序和质量衡量。数据货币化需要特定的程序、工具和能力，但最重要的是，需要一种促进创新产品开发的文化。数据货币化是关于开发新的业务线，拥有清晰的业务战略、有效的业务部门领导者和合格的员工至关重要。

机会

将 AI 引入数据处理的运动正在蓄势待发

组织被迫采用人工智能、物联网、机器学习和深度学习等新技术，因为它们会生成大量数据，并且需要实时评估这些数据。组织正在专注于部署 BI 技术，因为它可以非常有助于收集和分析大量数据。数据货币化解决方案可帮助您处理大量数据并从手头的信息中获得有用的见解。例如，许多公司使用 BI 工具，利用丰富的数据分析自己的产品、服务和客户行为模式。这些工具还用于分析大数据集并得出可用于开发市场机会和企业战略的分析见解。

威胁

复杂的数据结构

数据质量是数据货币化的关键考虑因素之一，它在各个行业无处不在，并带来新的商机。准确的数据使组织能够做出正确的决定。特定行业的数据共享和数据产品与现有系统的集成会降低数据质量。数据质量差会导致虚假事实和差异。因此，公司做出明智决策的能力直接受到数据质量的影响。没有质量，信息效率低下，并可能导致不可预测的结果。因此，预计组织获取的数据质量将难以利用数据货币化解决方案并限制数据货币化供应商的发展。

COVID-19 的影响

COVID-19 流行病导致开发新的解决方案，为客户提供预测性和规范性分析，简化业务流程以做出节省成本的决策。客户从这种数据货币化方法中获得最大价值，产品团队可以创建和部署与其他软件无缝集成的可操作分析应用程序。通过使用数据货币化技术和服务，企业可以获得可以增加数据价值的秘密信息。通过了解客户的购买行为和模式，这些工具和服务可以满足消费者的独特需求并改善整体客户体验。

工具部分预计将在预测期内成为最大的部分

预计工具部分将在预测期内占据最大的市场份额。业务应用程序采用数据货币化技术来改进功能，从业务数据中提取见解，并使企业能够做出明智的业务决策。数据货币化平台的既定功能支持跨技术集成结构化和非结构化数据。此外，数据货币化解决方案使数据货币化提供商能够通过提高满足客户特定要求的能力来增加市场份额并产生更多利润。

客户数据部分预计在预测期内见证最高的复合年增长率

客户数据部分在预测期内显示出最高的增长率。这是因为重要的消费者数据有助于公司製定战略。客户关係管理 (CRM) 系统允许企业从广告、调查、社交媒体和网站收集客户数据。借助客户数据，公司可以重塑自我并为其核心业务创造新的收入来源。了解目标市场的购买模式并分析产品设计和定价决策以便为客户定制产品和服务也很有用。例如，Facebook 分析用户数据并将其出售给外部公司，以便它可以展示为这些公司量身定制的广告。

市场占有率最高的地区

由于日本、中国和澳大利亚等国家人口众多，亚太地区预计在预测期内将占最大份额。因此，这些国家的企业需要快速实现数据货币化，以管理海量数据。此外，推动市场增长的主要因素是物联网、移动性、人工智能、云、顶级服务等数字服务的利用率不断提高，以及对该地区技术进步的投资不断增加。然而，由于众多中小微企业和大型企业的存在、业务运营的数字化程度不断提高以及产生的数据量不断增加，中国是该地区最赚钱的地区。

复合年增长率最高的地区：

由于物联网和云计算等尖端技术的利用率不断提高，亚太地区预计在整个预测期内将获得显着的增长机会。在亚太地区，公司数量正在增加。例如，新加坡有超过20万家公司。这是亚太地区增长率最高的主要原因之一。然而，在 BFSI、零售、医疗保健和生命科学行业的垂直整合中采用数据货币化工具将导致大数据和业务分析解决方案的出现，这些解决方案可以提高业务绩效、检测欺诈并在全球经济中保持竞争力。可能会加速通过大量投资

重大发展

2022 年 9 月，SAS 宣布其分析平台 Viya 现已在 Microsoft Azure Marketplace 上架。Microsoft Azure 上的 SAS Viya 的全部功能将为世界各地的客户提供访问数据探索、机器学习和模型部署的分析。该工具提供多种语言版本，并包含一个应用内学习中心以支持即时入门。Microsoft Azure 上的 SAS Viya 还将提供对完整 Viya 包的访问，包括 SAS Visual Analytics、SAS Visual Statistics、SAS Visual Data Mining、Machine Learning 和 SAS Model Manager。

2022 年 7 月，Google将推出新的维度和指标，以查看跳出率、额外的 UTM 参数值和跨各种表面的转化率，包括探索、细分、受众、报告和 Google Analytics Data API 现在可以

2022 年 6 月，英国民航局 (CAA) 将部署 Emu Analytics 的数字孪生解决方案 Flo.W，以监控英国领空的使用情况并提高安全性、效率和效率。针对未来做出明智的、数据驱动的决策所有空域用户，将他们考虑在内。

2022 年 1 月，Optiva, Inc. 和 Google Cloud 建立了多年战略合作伙伴关係。该合作伙伴关係旨在帮助运营商和服务提供商更好地拥抱数字化转型。

2021 年 8 月，Adastra 和 PaymentComponents 宣布即将建立合作伙伴关係，以在美国和加拿大提供先进的开放式银行和支付解决方案。Adastra 和 PaymentComponents 的综合实力将为客户提供可以有效推向市场的独特解决方案，从而增强后者作为该地区综合金融科技解决方案提供商的地位。

本报告提供的内容

  • 区域和国家级细分市场份额评估
  • 对新进入者的战略建议
  • 涵盖 2020、2021、2022、2025 和 2028 年的市场数据
  • 市场驱动因素（市场趋势、制约因素、机会、威胁、挑战、投资机会/建议等）
  • 基于市场估计的关键业务领域的战略建议
  • 竞争格局和趋势
  • 公司概况，包括详细战略、财务状况和近期发展
  • 供应链趋势反映了最新的技术进步。

提供免费定制

购买此报告的客户将免费获得以下定制之一。

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 个）
    • 关键参与者的 SWOT 分析（最多 3 个参与者）
  • 区域部分
    • 应客户要求提供主要国家/地区的市场估计、预测和 CAGR（注：不包括可行性检查。）
  • 竞争标桿

根据产品组合、地域分布和战略联盟对主要参与者进行基准测试

目录

第一章内容提要

第二章前言

  • 概述
  • 利益相关者
  • 调查范围
  • 调查方法
    • 数据挖掘
    • 数据分析
    • 数据验证
    • 研究方法
  • 研究来源
    • 主要研究来源
    • 二手研究资源
    • 假设

第三章市场趋势分析

  • 促进者
  • 抑製剂
  • 机会
  • 威胁
  • 最终用户分析
  • 新兴市场
  • COVID-19 的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5 全球数据货币化市场，按类型

  • 直接数据货币化
  • 间接数据货币化

6. 全球数据货币化市场，按组件

  • 服务
    • 咨询
    • 实施与整合
    • 支持和维护
  • 工具
  • 软件

7. 全球数据货币化市场，按数据类型

  • 供应商资料
  • 产品数据
  • 客户资料
  • 财务数据

8 全球数据货币化市场，按业务功能

  • 金融
  • 供应链管理
  • 销售与市场营销
  • 销售量
  • 其他业务功能

9 全球数据货币化市场，按部署类型

  • 本地
  • 云

10 全球数据货币化市场，按组织规模

  • 中小企业
  • 大公司

11 全球数据货币化市场：按方法

  • 即服务即服务
  • 嵌入式分析
  • 数据即服务
  • 服务即服务

12. 全球数据货币化市场，按最终用户分类

  • 沟通
  • 银行、金融服务、保险
  • 信息技术
  • 消费品和零售
  • 製造业
  • 卫生保健
  • 运输
  • 媒体和娱乐
  • 能源和公用事业
  • 其他最终用户

13. 全球数据货币化市场，按地区

  • 北美
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 意大利
    • 法国
    • 西班牙
    • 欧洲其他地区
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳大利亚
    • 新西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美洲
  • 中东和非洲
    • 沙特阿拉伯
    • 阿拉伯联合酋长国
    • 卡塔尔
    • 南非
    • 其他中东

第 14 章主要进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务拓展
  • 其他关键策略

第十五章公司简介

  • 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.