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市場調查報告書
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1456927

資料收益市場 - 2024 年至 2029 年預測

Data Monetization Market - Forecasts from 2024 to 2029
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 152 Pages | 商品交期: 最快1-2個工作天內

價格
簡介目錄

2022年資料收益市場規模為1,999.82億美元，預估2029年將達3,073.03億美元，預測期間內複合年成長率為6.33%。

資料收益是公司之間共用資料的過程。業務數位化的快速採用、企業資料量的增加、對資料收益潛在好處的認知不斷提高以及市場上營運的主要企業的巨額投資預計將推動市場的成長。例如，Uber、Lyft 和 Ola 等叫車公司使用位置分析來收集與從接送地點提取的客戶資料相關的資訊。 Uber 和 Ola 等公司在獲得您的許可後，會將這些資料出售給其他組織和公司。其他公司也可以使用這些資料來提供各種優惠券、促銷和折扣，鼓勵消費者在其產品上花錢。

雲端處理在世界各地的普及正在推動市場發展。

支持整體市場成長的關鍵原因之一是全球擴大採用雲端技術。各國政府正做出巨大努力，擴大物聯網、雲端運算和人工智慧等尖端技術的採用。例如，新加坡政府推出了政府商業雲端服務，將商業雲端處理平台的創新和能力帶入非敏感政府系統。各個已開發國家的電訊營運商也正在採用雲端技術來實現業務成長並向最終用戶提供雲端服務，我們相信這將進一步推動預測期內對資料收益解決方案和服務的需求。此外，組織擴大轉向採用數位轉型預計將推動雲端處理服務的採用，從而推動整體市場的成長。

此外，根據網路電信聯盟公佈的資料，2022年網路用戶將達51億，2023年將增加至54億。網路世界的普及預計將產生大量資料並增加對資料收益服務的需求。此外，所有醫療保健主管將用於結果預測的人工智慧投資從 2021 年的 30% 增加到 2023 年的 39%。此外，根據飛利浦未來健康指數報告，到 2023 年，39% 的醫療保健主管打算投資人工智慧 (AI) 來預測結果，高於 2021 年的 30%。

此外，邊緣運算、人工智慧和物聯網等先進技術的日益使用也進一步推動了資料收益服務的採用。例如，加拿大在2021年聯邦預算中大力投資人工智慧，宣布將投資1.85億美元支持人工智慧研究的商業化。該投資是為了支持泛加拿大人工智慧策略，預計 10 年內將達到 4.438 億美元，並對整體市場成長產生積極影響（資料來源：ITA）。

預計北美地區市場將會成長。

在新興經濟體正在發展的美國，數位化迅速提高，競爭日益加劇，對資料收益服務的需求不斷增加，加上物聯網、巨量資料、人工智慧的快速採用。市場正在迅速適應和發展，以滿足不斷變化的智慧商業服務需求。一些市場參與企業正在擴大規模，以滿足新的需求並提供更好的服務和解決方案。資料收益平台 UBDI 與 AXIA 於 2021 年 7 月的合作就是一個例子。透過這種合作關係，AXIA 成功地實現了貨幣民主化，讓用戶能夠更好地控制自己的資料，並以新穎且創造性的方式將其貨幣化。展望未來，兩家公司都計劃利用彼此的基礎設施來建立對用戶至關重要的新工具。

在當今的數位時代，第一方資料的規模是許多品牌目前正在努力解決的關鍵問題之一。日益嚴重的隱私問題和即將訂定的有關消費者識別資訊的法規正在加劇這種情況。提供符合當前隱私規則的強大身分驗證解決方案工具，資料對於各種規模的企業進行決策、分析市場趨勢、減少損失、增加利潤已經變得至關重要。利用這種成長，該地區的許多新興企業也迅速進入市場，進一步加劇了市場競爭。在美國，主要新興企業包括 Instrematic、Frame AI、OctoML 和 PostEra。同時，由於資料和多個相關行業的成長，資料科學家或分析分析師的角色已成為最受歡迎的職業。例如，根據美國勞工統計局的數據，截至 2021 年 5 月，該國約有 105,980 名資料科學家，反映了市場對資料重要性的需求。

主要市場開拓：

  • 領先的 IT 公司 Tata Consultancy Services (TCS) 於 2023 年 6 月在 Google Cloud 上推出了 TCS Dexam資料市場平台。該公司表示，該平台將透過確保遵守資料同意、隱私和收益法規，實現企業資料的民主化和貨幣化，同時為企業及其生態系統合作夥伴提供持續的資料交換。
  • John Snow Labs 是一家開發 Spark NLP 庫的醫療 AI 和 NLPStart-Ups，於 2022 年 10 月推出了其自動去識別系統的增強功能。 John Snow Labs 協助世界各地的醫療保健組織自動將大型資料集去識別化，以推動產品創新並降低成本。資料收益所需的自訂去識別識別由該公司的自動去識別解決方案提供。
  • 2022 年 6 月，我們宣布 Google Cloud 與 Palantir 建立合作關係。業務的成功取決於有效處理資料的能力，隨著世界變得更加複雜，將分析轉化為改進的決策和結果。為了解決這種複雜性，Palantir 和 Google Cloud 將利用後者的分析、人工智慧和機器學習功能來推動業務決策，並為前者的商業客戶提供端到端資料解決方案。這使得第一線業務用戶、IT 和技術專家之間能夠更快地實現價值，使每個人都能更有效地利用資料，同時幫助客戶主導資料驅動型轉型。
  • BDEX 和 InfoSum 2021 年 2 月，領先的 ID 基礎設施供應商 InfoSum 與 BDEX 建立合作夥伴關係。由於新的合作夥伴關係，InfoSum 客戶現在可以存取 BDEX 廣泛的身份圖和其他資料資產，從而使他們能夠產生目標受眾並產生對第一方資料的新見解，同時保護消費者隱私。

主要參與企業

  • 埃森哲是一位著名的參與企業，提供一系列旨在幫助企業從資料資產中獲取價值的服務。埃森哲利用先進的分析、人工智慧和機器學習功能來幫助您最佳化資料策略，以產生收入並提高業務效率。埃森哲是一家以創新而聞名的全球性公司，為各行業提供專業的解決方案。
  • Adastra 專門為希望最大限度地發揮資料潛力並收益的企業提供資料管理和分析解決方案。 Adastra 專注於資料管治、整合和質量，使公司能夠將原始資料轉化為可操作的見解，從而推動收益成長和競爭優勢。透過結合尖端技術和行業專業知識，Adastra 幫助客戶釋放其資料資產的價值，同時確保遵守監管標準和隱私法規。 Adastra 是資料收益領域值得信賴的合作夥伴，幫助企業駕馭複雜的資料生態系統並利用數位市場的新機會。
  • Infosys 是一家全球領先的諮詢和技術服務公司，為世界各地的企業提供全面的資料收益解決方案。憑藉雲端運算、分析和數位轉型的專業知識，印孚瑟斯幫助企業釋放資料資產的價值，推動收益成長和創新。透過利用先進的分析、機器學習和人工智慧功能，Infosys 幫助客戶從資料中獲得可行的見解，做出明智的決策，並利用新興市場趨勢。 Infosys 專注於提供可衡量的業務成果，幫助企業有效地將資料資產收益，並在當今資料驅動的經濟中競爭。

目錄

第1章 簡介

  • 市場概況
  • 市場定義
  • 調查範圍
  • 市場區隔
  • 貨幣
  • 先決條件
  • 基準年和預測年時間表
  • 相關人員的主要利益

第2章調查方法

  • 研究設計
  • 調查過程

第3章執行摘要

  • 主要發現
  • 分析師觀點

第4章市場動態

  • 市場促進因素
  • 市場限制因素
  • 波特五力分析
  • 產業價值鏈分析
  • 分析師觀點

第5章資料收益市場：依產品類型

  • 介紹
  • 解決方案
  • 服務

第6章資料收益市場：依部署模型

  • 介紹
  • 本地
  • 雲

第7章資料收益市場：依公司規模

  • 介紹
  • 小的
  • 期間~
  • 大的

第8章資料收益市場：按最終用戶產業

  • 介紹
  • 零售
  • 製造業
  • 車
  • 英國
  • 媒體和娛樂
  • 其他

第9章資料收益市場：按地區

  • 介紹
  • 北美洲
  • 南美洲
  • 歐洲
  • 中東/非洲
  • 亞太地區

第10章競爭環境及分析

  • 主要企業及策略分析
  • 市場佔有率分析
  • 合併、收購、協議和合作
  • 競爭對手儀表板

第11章 公司簡介

  • Accenture
  • First Quantum（Adastra）
  • Dawex Systems
  • Elevondata
  • EMU Analytics
  • Gemalto NV（Thales Group）
  • Infosys
  • MonetizeMore
  • IBM
  • Google
  • SAP
  • SAS AB
簡介目錄
Product Code: KSI061612184

The data monetization market was valued at US$199.982 billion in 2022 and is projected to expand at a CAGR of 6.33% over the forecast period to reach US$307.303 billion by 2029.

Data monetization is the process in which the data is shared between companies. The rapid adoption of digitization of businesses, rise in enterprise data volume, growing awareness towards the potential benefits of data monetization, and huge investments by key players operating in the market are anticipated to drive the market growth. For instance, ride-hailing companies such as Uber, Lyft, and Ola use location-based analytics to gather information related to their customer's data that is extracted from pick-up and drop locations. Companies such as Uber and Ola sell this data to other organizations or businesses with the user's permission. This data can be further used by other companies to provide different vouchers, promotions, or discounts that encourage consumers to spend money on their products.

The rising adoption of cloud computing worldwide propels the market.

One of the prime reasons supporting the growth of the overall market growth is the increasing adoption of cloud technology worldwide. The governments of various countries are making huge efforts to increase the adoption of advanced technologies such as IoT, cloud computing, and AI. For instance, the Singapore government has launched the Government Commercial Cloud Service that will introduce the innovations and capabilities of commercial cloud computing platforms to less sensitive government systems. Telecom providers in various developed nations are also adopting cloud technology for the growth of their businesses and to provide cloud services to end-users which will further augment the demand for data monetization solutions and services during the forecast period. Additionally, the increasing shift of organizations towards the adoption of digital transformation is expected to drive the adoption of cloud computing services, which in turn is anticipated to drive the overall market growth.

Furthermore, according to the data published by Internet Telecom Union, the number of Internet users in 2022 was 5.1 billion which has increased to 5.4 billion in 2023. Growing penetration of the internet globally is anticipated to generate huge data which will increase the demand for data monetization services. Additionally, all healthcare executives increased their projected investments in AI for outcome prediction, from 30% in 2021 to 39% in 2023. Moreover, in 2023, 39% of healthcare executives intend to invest in artificial intelligence (AI) to predict outcomes, up from 30% in 2021, according to the Philips Future Health Index report.

Moreover, the growing use of advanced technologies, such as edge computing, AI, and the Internet of Things, is further augmenting the adoption of data monetization services. For instance, Canada is making a significant investment in Artificial Intelligence in its federal budget for 2021 the country has announced that it will invest $185 million to support the commercialization of AI research. The investments are made to support the Pan-Canadian Artificial Intelligence Strategy to $443.8 million over 10 years which is anticipated to have a positive impact on the overall market growth (Source: ITA).

The market is projected to grow in the North American region.

The well-developed economies, rapidly growing digitalization and competitively advancing technologies in the United States of America, coupled with the swift adoption of IoT, big data, and AI, are propelling the demand for data monetization services. The market is rapidly adapting and evolving to meet the changing demands of smart business services. Amid such a scenario, multiple market players are scaling up to meet the emerging demands and offer better services and solutions. The collaboration between the data monetization platform UBDI and AXIA in July 2021 is another example. The partnership has helped advance AXIA's efforts to democratize money, giving the users more control over their data and monetizing it in fresh and creative ways. Together, the duo intends to be able to take advantage of one another's infrastructure to build vital new tools for users.

In the present digital era, the size of their first-party data is one of the main issues that many brands are currently dealing with. The growing privacy concerns and impending restrictions on consumer identifiers have made this situation much worse. To provide a potent identity resolution tool that complies with the current privacy rules, Data has become indispensable value for businesses of all sizes to make decisions, analyze market trends, reduce losses, and increase profits. Exploiting this growth, many start-ups in the region are also rapidly emerging in the market, making it even more competitive. Instrematic, Frame AI, OctoML, and PostEra are a few major start-ups in the United States. At the same time, the roles of a Data Scientist and research analyst has become the most sought-after profession due to the increase in data and in multiple connected industries. For instance, according to the US Bureau of Labor Statistics, there are about 105,980 data scientists in the country as of May 2021, reflecting the need for the importance of data in the market.

Key Market Developments:

  • Leading IT firm Tata Consultancy Services (TCS) introduced the TCS Dexam data marketplace platform on Google Cloud in June 2023. The platform, according to the company, ensures compliance with data consent, privacy, and security regulations while enabling enterprises to democratize and monetize data by offering a continuous data exchange for enterprises and their ecosystem partners.
  • John Snow Labs, the Healthcare AI and NLP startup that created the Spark NLP library, revealed enhancements to its automated de-identification system in October 2022. John Snow Labs helps healthcare organizations all over the world to automatically de-identify large datasets, empowering product innovation and cost savings. Custom de-identification needed for data monetization is provided by the company's automatic de-identification solution.
  • Partnership announced between Google Cloud and Palantir in June 2022. Business success depends on the ability to efficiently handle data while converting analysis into improved decisions and results as the world becomes more complicated. To deal with such complexities, Palantir and Google Cloud announced their partnership to offer the former's commercial customers an end-to-end data solution, enhancing operational decision-making with the latter's analytics, artificial intelligence, and machine learning capabilities. This will enable data-driven transformation for its clients while providing a quick time-to-value link between front-line business users, IT, and technical experts, enabling them all to use their data more effectively
  • BDEX and InfoSum have teamed up in February 2021, leading identity infrastructure supplier InfoSum and BDEX entered into a partnership. As a result of the new partnership, InfoSum clients were able to access BDEX's extensive identity graph and other data assets, allowing them to generate targeted audiences and gain fresh insights into their first-party data while protecting the privacy of those consumers.

Key Players:

  • Accenture is a prominent player, offering a range of services aimed at helping businesses extract value from their data assets. Leveraging advanced analytics, artificial intelligence, and machine learning capabilities, Accenture assists clients in optimizing their data strategies to drive revenue generation and improve operational efficiency. With a strong global presence and a reputation for innovation, Accenture delivers tailored solutions to various industries, empowering organizations to unlock insights, enhance decision-making processes, and capitalize on emerging opportunities in the rapidly evolving data economy.
  • Adastra specializes in data management and analytics solutions, catering to businesses seeking to harness the full potential of their data for monetization purposes. With a focus on data governance, integration, and quality, Adastra enables organizations to transform raw data into actionable insights, driving revenue growth and competitive advantage. Through a combination of cutting-edge technologies and industry expertise, Adastra empowers clients to unlock the value of their data assets while ensuring compliance with regulatory standards and privacy regulations. As a trusted partner in the data monetization space, Adastra helps businesses navigate complex data ecosystems and capitalize on emerging opportunities in the digital marketplace.
  • Infosys is a leading global consulting and technology services firm that offers comprehensive data monetization solutions to enterprises worldwide. Leveraging its expertise in cloud computing, analytics, and digital transformation, Infosys assists organizations in unlocking the value of their data assets to drive revenue growth and innovation. By harnessing advanced analytics, machine learning, and artificial intelligence capabilities, Infosys helps clients derive actionable insights from their data, enabling them to make informed decisions and capitalize on emerging market trends. With a focus on delivering measurable business outcomes, Infosys empowers businesses to monetize their data assets effectively, gaining a competitive edge in today's data-driven economy.

Segmentation:

By Offering Type:

  • Solution
  • Services

By Deployment Model:

  • On-Premise
  • Cloud

By Enterprise Size:

  • Small
  • Medium
  • Large

By End-User Industry:

  • Retail
  • Manufacturing
  • Automotive
  • BFSI
  • Media and Entertainment
  • Others

By Geography

  • North America
  • United States
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Israel
  • Others
  • Asia Pacific
  • Japan
  • China
  • India
  • South Korea
  • Indonesia
  • Thailand
  • Others

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. Market Overview
  • 1.2. Market Definition
  • 1.3. Scope of the Study
  • 1.4. Market Segmentation
  • 1.5. Currency
  • 1.6. Assumptions
  • 1.7. Base, and Forecast Years Timeline
  • 1.8. Key benefits for the stakeholders

2. RESEARCH METHODOLOGY

  • 2.1. Research Design
  • 2.2. Research Process

3. EXECUTIVE SUMMARY

  • 3.1. Key Findings
  • 3.2. Analyst View

4. MARKET DYNAMICS

  • 4.1. Market Drivers
  • 4.2. Market Restraints
  • 4.3. Porter's Five Forces Analysis
    • 4.3.1. Bargaining Power of Suppliers
    • 4.3.2. Bargaining Power of Buyers
    • 4.3.3. Threat of New Entrants
    • 4.3.4. Threat of Substitutes
    • 4.3.5. Competitive Rivalry in the Industry
  • 4.4. Industry Value Chain Analysis
  • 4.5. Analyst View

5. DATA MONETIZATION MARKET BY OFFERING TYPE

  • 5.1. Introduction
  • 5.2. Solution
    • 5.2.1. Market Trends and Opportunities
    • 5.2.2. Growth Prospects
    • 5.2.3. Geographic Lucrativeness
  • 5.3. Services
    • 5.3.1. Market Trends and Opportunities
    • 5.3.2. Growth Prospects
    • 5.3.3. Geographic Lucrativeness

6. DATA MONETIZATION MARKET BY DEPLOYMENT MODEL

  • 6.1. Introduction
  • 6.2. On-Premise
    • 6.2.1. Market Trends and Opportunities
    • 6.2.2. Growth Prospects
    • 6.2.3. Geographic Lucrativeness
  • 6.3. Cloud
    • 6.3.1. Market Trends and Opportunities
    • 6.3.2. Growth Prospects
    • 6.3.3. Geographic Lucrativeness

7. DATA MONETIZATION MARKET BY ENTERPRISE SIZE

  • 7.1. Introduction
  • 7.2. Small
    • 7.2.1. Market Trends and Opportunities
    • 7.2.2. Growth Prospects
    • 7.2.3. Geographic Lucrativeness
  • 7.3. Medium
    • 7.3.1. Market Trends and Opportunities
    • 7.3.2. Growth Prospects
    • 7.3.3. Geographic Lucrativeness
  • 7.4. Large
    • 7.4.1. Market Trends and Opportunities
    • 7.4.2. Growth Prospects
    • 7.4.3. Geographic Lucrativeness

8. DATA MONETIZATION MARKET BY END-USER INDUSTRY

  • 8.1. Introduction
  • 8.2. Retail
    • 8.2.1. Market Trends and Opportunities
    • 8.2.2. Growth Prospects
    • 8.2.3. Geographic Lucrativeness
  • 8.3. Manufacturing
    • 8.3.1. Market Trends and Opportunities
    • 8.3.2. Growth Prospects
    • 8.3.3. Geographic Lucrativeness
  • 8.4. Automotive
    • 8.4.1. Market Trends and Opportunities
    • 8.4.2. Growth Prospects
    • 8.4.3. Geographic Lucrativeness
  • 8.5. BFSI
    • 8.5.1. Market Trends and Opportunities
    • 8.5.2. Growth Prospects
    • 8.5.3. Geographic Lucrativeness
  • 8.6. Media and Entertainment
    • 8.6.1. Market Trends and Opportunities
    • 8.6.2. Growth Prospects
    • 8.6.3. Geographic Lucrativeness
  • 8.7. Others
    • 8.7.1. Market Trends and Opportunities
    • 8.7.2. Growth Prospects
    • 8.7.3. Geographic Lucrativeness

9. DATA MONETIZATION MARKET BY GEOGRAPHY

  • 9.1. Introduction
  • 9.2. North America
    • 9.2.1. By Offering Type
    • 9.2.2. By Enterprise Size
    • 9.2.3. By Development Mode
    • 9.2.4. By End-User Industry
    • 9.2.5. By Country
      • 9.2.5.1. United States
        • 9.2.5.1.1. Market Trends and Opportunities
        • 9.2.5.1.2. Growth Prospects
      • 9.2.5.2. Canada
        • 9.2.5.2.1. Market Trends and Opportunities
        • 9.2.5.2.2. Growth Prospects
      • 9.2.5.3. Mexico
        • 9.2.5.3.1. Market Trends and Opportunities
        • 9.2.5.3.2. Growth Prospects
  • 9.3. South America
    • 9.3.1. By Offering Type
    • 9.3.2. By Enterprise Size
    • 9.3.3. By Development Mode
    • 9.3.4. By End-User Industry
    • 9.3.5. By Country
      • 9.3.5.1. Brazil
        • 9.3.5.1.1. Market Trends and Opportunities
        • 9.3.5.1.2. Growth Prospects
      • 9.3.5.2. Argentina
        • 9.3.5.2.1. Market Trends and Opportunities
        • 9.3.5.2.2. Growth Prospects
      • 9.3.5.3. Others
        • 9.3.5.3.1. Market Trends and Opportunities
        • 9.3.5.3.2. Growth Prospects
  • 9.4. Europe
    • 9.4.1. By Offering Type
    • 9.4.2. By Enterprise Size
    • 9.4.3. By Development Mode
    • 9.4.4. By End-User Industry
    • 9.4.5. By Country
      • 9.4.5.1. United Kingdom
        • 9.4.5.1.1. Market Trends and Opportunities
        • 9.4.5.1.2. Growth Prospects
      • 9.4.5.2. Germany
        • 9.4.5.2.1. Market Trends and Opportunities
        • 9.4.5.2.2. Growth Prospects
      • 9.4.5.3. France
        • 9.4.5.3.1. Market Trends and Opportunities
        • 9.4.5.3.2. Growth Prospects
      • 9.4.5.4. Italy
        • 9.4.5.4.1. Market Trends and Opportunities
        • 9.4.5.4.2. Growth Prospects
      • 9.4.5.5. Spain
        • 9.4.5.5.1. Market Trends and Opportunities
        • 9.4.5.5.2. Growth Prospects
      • 9.4.5.6. Others
        • 9.4.5.6.1. Market Trends and Opportunities
        • 9.4.5.6.2. Growth Prospects
  • 9.5. Middle East and Africa
    • 9.5.1. By Offering Type
    • 9.5.2. By Enterprise Size
    • 9.5.3. By Development Mode
    • 9.5.4. By End-User Industry
    • 9.5.5. By Country
      • 9.5.5.1. Saudi Arabia
        • 9.5.5.1.1. Market Trends and Opportunities
        • 9.5.5.1.2. Growth Prospects
      • 9.5.5.2. UAE
        • 9.5.5.2.1. Market Trends and Opportunities
        • 9.5.5.2.2. Growth Prospects
      • 9.5.5.3. Israel
        • 9.5.5.3.1. Market Trends and Opportunities
        • 9.5.5.3.2. Growth Prospects
      • 9.5.5.4. Others
        • 9.5.5.4.1. Market Trends and Opportunities
        • 9.5.5.4.2. Growth Prospects
  • 9.6. Asia Pacific
    • 9.6.1. By Offering Type
    • 9.6.2. By Enterprise Size
    • 9.6.3. By Development Mode
    • 9.6.4. By End-User Industry
    • 9.6.5. By Country
      • 9.6.5.1. Japan
        • 9.6.5.1.1. Market Trends and Opportunities
        • 9.6.5.1.2. Growth Prospects
      • 9.6.5.2. China
        • 9.6.5.2.1. Market Trends and Opportunities
        • 9.6.5.2.2. Growth Prospects
      • 9.6.5.3. India
        • 9.6.5.3.1. Market Trends and Opportunities
        • 9.6.5.3.2. Growth Prospects
      • 9.6.5.4. South Korea
        • 9.6.5.4.1. Market Trends and Opportunities
        • 9.6.5.4.2. Growth Prospects
      • 9.6.5.5. Indonesia
        • 9.6.5.5.1. Market Trends and Opportunities
        • 9.6.5.5.2. Growth Prospects
      • 9.6.5.6. Thailand
        • 9.6.5.6.1. Market Trends and Opportunities
        • 9.6.5.6.2. Growth Prospects
      • 9.6.5.7. Others
        • 9.6.5.7.1. Market Trends and Opportunities
        • 9.6.5.7.2. Growth Prospects

10. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 10.1. Major Players and Strategy Analysis
  • 10.2. Market Share Analysis
  • 10.3. Mergers, Acquisition, Agreements, and Collaborations
  • 10.4. Competitive Dashboard

11. COMPANY PROFILES

  • 11.1. Accenture
  • 11.2. First Quantum (Adastra)
  • 11.3. Dawex Systems
  • 11.4. Elevondata
  • 11.5. EMU Analytics
  • 11.6. Gemalto NV (Thales Group)
  • 11.7. Infosys
  • 11.8. MonetizeMore
  • 11.9. IBM
  • 11.10. Google
  • 11.11. SAP
  • 11.12. SAS AB