Data Monetization Market

Data Monetization Market by Component (Tools and Services), Data Type, Business Function, Deployment Type (On-Premises and Cloud), Organization Size, Industry Vertical (BFSI, Consumer Goods and Retail, and Telecom), and Region - Global Forecast to 2023

Report Code: TC 6282 May, 2018, by marketsandmarkets.com
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[158 Pages Report] In a digitalized world, data is an important asset for firms. The proliferation of businesses worldwide has generated large volumes of data within organizations. To get actionable insights from the data and generate new revenue streams is termed as data monetization. Data monetization tools integrate big data and analytics capabilities to empower enterprises to monetize the data generated from various departments, such as sales and marketing, supply chain management, operations, and finance. Data monetization tools and services help enterprises extract concealed information, which can add value to the business data. Moreover, these tools and services enhance the operational efficiency of an enterprise by predicting the anomalies faster in a business cycle. These tools and services also enable organizations serve consumers’ intrinsic needs by comprehending consumers’ buying behavior and patterns, thereby enhancing the overall customer experience.

These tools and services are not new to organizations; however, from the last decade, they have gained traction, owing to the focus of companies on correlating data and gaining business insights. Declining revenue-per-bit and the competition from non-traditional players have led organizations to adopt data monetization services for diversifying their revenues, preventing revenue leakage, and building a more competitive advantage through innovation.

The data monetization market is expected to grow from USD 1.42 billion in 2018 to USD 3.12 billion by 2023, at a CAGR of 17.1% during the forecast period.

Data Monetization Market

By component, the tools segment is expected to hold the larger market size during the forecast period

The tools segment is estimated to dominate the data monetization market with a larger market size during the forecast period. Data monetization tools help streamline business processes, enhance decision-making, and generate new revenue streams across various industry verticals, thereby contributing to the larger market size.

By data type, the financial data type is expected to grow at the highest CAGR during the forecast period, as the financial data type is widely used by organizations to define new business strategies for their growth.

By business function, the sales and marketing segment is expected to grow at the highest CAGR during the forecast period, as marketers need to unlock consumer insights and plan strategies to roll out data-driven campaigns for the increasing revenues.

Data Monetization Market

By region, North America is expected to have the largest market size during the forecast period. The region has some of the most powerful multinational corporates, such as IBM, Reltio, ALC, Paxata, SAS, Google, and Openwave Mobility. Moreover, factors such as the inclination of organizations toward ease-of-use methods for decision-making processes and the advent of advanced technologies, such as big data and IoT, are expected to catalyze the growth of the data monetization market.

Data Monetization Market

Market Dynamics

Driver: Increasing use of external data sources

External data can serve multiple purposes; social media (Facebook, Twitter, and Instagram) data provides insights into the behavior and beliefs of individual users or a demographic group. Professional media data (such as LinkedIn and Glassdoor) provides an alternate perspective of an individual’s beliefs and values. News media or weather data provides insights into events, trends, and patterns that could externally influence an individual. Therefore, organizations are constantly looking for new and innovative ways to generate new revenue streams and minimize their operating expenses. By leveraging the external data sources, organizations can gain valuable insights into the existing customers and prospects, which would ultimately help them increase their market share and gain a competitive advantage over their rivals.

Restraint:  Organizational capabilities and culture

One of the major barriers related to big data utilization is not technology-related; it is related to the organizational capabilities and culture. Barriers such as lack of sufficient roles and responsibilities, inefficient organizational procedures, lack of management’s focus and support, and missing procedures and quality measurements are expected to act as restraining factors for the implementing data monetization tools. Data monetization requires a specific set of processes, resources, and skills, and most importantly, a suitable culture that sufficiently supports the creation of new offerings. To derive new revenue streams and monetize the data, a clear business strategy and a strong business unit leader with a capable team is the need of the hour, as data monetization is all about creating a new line of business. It is not sufficient to provide the right data set and relevant tools to employees. It is also necessary to brief the employee about the company’s culture, organizational structure, and the required capabilities, processes, and habits that are needed to support the chosen data monetization business model.

Opportunity: Increasing adoption of AI for data processing

The generation of massive amounts of data and the need to analyze this data in real-time has compelled organizations to adopt new technologies, such as AI. Organizations are focusing on adopting BI tools, as they are highly useful in collecting and processing huge amounts of data. Moreover, data monetization solutions can process huge amounts of data and help extract valuable insights from the available data. Nowadays, to gain a dominant position in the market, companies have started adopting BI tools. For instance, various organizations are taking the advantage of the BI tools to analyze their products, services, and customer behavioral patterns from a huge amount of data, as well as, to analyze large data sets and derive analytical insights, which could be used to identify market opportunities and potential threats while also formulating business strategies. As organizations are looking for solutions to meet these requirements, data monetization solutions can come handy for data management and integration solutions. Moreover, these BI tools and the data monetization technology can help business users meet the analytical requirements and intelligence that is needed to stay competitive in the data monetization market. Therefore, the growing use of BI tools can be seen as an opportunity for the growth of the data monetization vendors.

Challenge:  Increasing complexities in data structures

Earlier, enterprises used to generate data (sales and inventory data) from their own businesses. However, in today’s era, the data collected and analyzed by enterprises has surpassed this scope. The large amounts of data coming from various sources, such as internet and mobile web; IoT; various industries; and scientific, experimental, and observational processes, produce energy data, biological data, and space observation data. These data sources generate various data types, such as unstructured data that includes documents, videos, and audios; semi-structured data that includes software packages/modules, spreadsheets, and financial reports; and structured data such as conversion data, syndicated industry data, production and distribution data. The quantity of unstructured data occupies more than 80% of the total amount of data in existence.

As the data is collected from different sources, integrating them effectively is a daunting task, and there is a possibility of conflicts and inconsistencies among data from different sources. The huge amount of data processed by data monetization solutions is extracted from structured data sources, such as tabular data from Relational Database Management Systems (RDBMSs) and an organization’s database, which is not structured. When this complex data is integrated, data quality problems result. Therefore, this is expected to be one of the challenging factors in implementing data monetization solutions.

Scope of the Report

Report Metric

Details

Market size available for years

2016–2023

Base year considered

2017

Forecast period

2018–2023

Forecast units

USD million

Segments covered

Component, Data Type, Business Function, Deployment Type, Organization Size, Industry & Region

Geographies covered

North America (US, Canada), Europe (Germany, France, UK, and Rest of Europe), Asia Pacific (China, Japan, Australia & New Zealand, Singapore, and Rest of Asia Pacific), Middle East and Africa (South Africa, Kingdom of Saudi Arabia, UAE, Rest of MEA), and Latin America (Brazil, Mexico, Rest of Latin America)

Companies covered

1010data (US), Accenture (Ireland), Adastra (Canada), Cisco (US), Dawex (France), Elevondata (US), Emu Analytics (UK), Gemalto (Netherlands), Google (US), IBM (US), iConnectiva (Hong Kong), Infosys (India), Mahindra Comviva (India), Monetize Solutions (US), Narrative (US), NESS (US), NETSCOUT (US), Openwave Mobility (US), Optiva (Canada),  Paxata (US), Reltio (US), SAP (Germany), SAS (US), and Virtusa (US)

The research report categorizes the data monetization market to forecast the revenues and analyze the trends in each of the following submarkets:

By Component

  • Tools
  • Services
    • Support and maintenance
    • Consulting
    • Implementation

By Data Type

  • Customer data
  • Product data
  • Financial data
  • Supplier data

By Business Function

  • Sales and marketing
  • Supply chain management
  • Operations
  • Finance
  • Others (R&D, HR, and legal)

By Deployment Type

  • On-premises
  • Cloud

By Organization Size

  • Small and Medium-sized Enterprises (SMEs)
  • Large enterprises

By Industry Vertical

  • Banking, Financial Services, and Insurance (BFSI)
  • Telecom
  • Consumer goods and retail
  • Media and entertainment
  • Government and defense
  • Manufacturing
  • Transportation and logistics
  • Energy and utilities
  • Healthcare
  • Others (real estate, education, and travel and hospitality)

By Region

  • North America
  • Europe
  • MEA
  • APAC
  • Latin America

Key Market Players

IBM, Accenture, SAP, Infosys, SAS

Recent Developments

  • In April 2018, SAS enhanced the capability of its business analytics platform by integrating AI capabilities into its flagship product, SAS analytics platform.
  • In March 2018, IBM launched Cloud Private for Data, a new data science and machine learning platform for data-driven decision-making.
  • In February 2018, Reltio launched a new version of Reltio’s self-learning data platform-as-a-service that combines machine learning capabilities with advanced analytics.
  • In October 2017, Dawex Systems partnered with Mnubo, a leading vendor in IoT analytics and AI-as-a-service. This partnership enabled Mnubo to link its SmartObjects analytics solution to Dawex’s data marketplace to provide product insights and data monetization opportunities for IoT manufacturers and service providers.
  • In April 2017, Adastra acquired Anywhere Mobile Apps, a mobile application developing specialist. This acquisition expands the services portfolio, built on data warehouses, big data, advanced data analysis, and solutions for IoT.

Critical questions the report answers:

  • Which end-user segment is expected to witness maximum growth opportunities during the forecast period?
  • Which would be the leading region to experience the highest CAGR during the forecast period?
  • How many companies implementing organic and inorganic growth strategies could gain an increased market share?
  • Who are the key players operating in the market, and what are the factors contributing to their domination over other players?

To speak to our analyst for a discussion on the above findings, click Speak to Analyst

Table of Contents

1 Introduction (Page No. - 17)
    1.1 Objectives of the Study
    1.2 Market Definition
    1.3 Market Scope
    1.4 Years Considered for the Study
    1.5 Currency
    1.6 Stakeholders

2 Research Methodology (Page No. - 21)
    2.1 Research Data
           2.1.1 Secondary Data
           2.1.2 Primary Data
                    2.1.2.1 Breakdown of Primaries
                    2.1.2.2 Key Industry Insights
    2.2 Market Size Estimation
    2.3 Research Assumptions
    2.4 Limitations

3 Executive Summary (Page No. - 27)

4 Premium Insights (Page No. - 30)
    4.1 Attractive Market Opportunities in the Data Monetization Market
    4.2 Market By Component
    4.3 Market By Deployment Type
    4.4 Market Top 3 Industry Verticals and Regions (2018)
    4.5 Market By Organization Size

5 Data Monetization Market Overview and Industry Trends (Page No. - 33)
    5.1 Introduction
    5.2 Market Dynamics
           5.2.1 Drivers
                    5.2.1.1 Rapid Adoption of Advanced Analytics and Visualization
                    5.2.1.2 Increasing Use of External Data Sources
                    5.2.1.3 Increasing Adoption of Data-Driven Decision-Making
                    5.2.1.4 Increasing Volume and Variety of Business Data
           5.2.2 Restraints
                    5.2.2.1 The Varying Structure of Regulatory Policies
                    5.2.2.2 Organizational Capabilities and Culture
           5.2.3 Opportunities
                    5.2.3.1 Increasing Need to Create Insights From A Pool of Data
                    5.2.3.2 Increasing Adoption of Ai for Data Processing
           5.2.4 Challenges
                    5.2.4.1 Privacy and Security Aspects
                    5.2.4.2 Increasing Complexities in Data Structures
    5.3 Industry Trends
           5.3.1 Data Monetization Use Cases
                    5.3.1.1 Use Case 1: Telecommunication
                    5.3.1.2 Use Case 2: Media and Entertainment
                    5.3.1.3 Use Case 3: BFSI
                    5.3.1.4 Use Case 4: Automobile
                    5.3.1.5 Use Case 5: Telecommunication

6 Data Monetization Market, By Component (Page No. - 40)
    6.1 Introduction
    6.2 Tools
    6.3 Services
           6.3.1 Consulting
           6.3.2 Support and Maintenance
           6.3.3 Implementation

7 Market, By Data Type (Page No. - 45)
    7.1 Introduction
    7.2 Customer Data
    7.3 Product Data
    7.4 Financial Data
    7.5 Supplier Data

8 Data Monetization Market, By Business Function (Page No. - 51)
    8.1 Introduction
    8.2 Sales and Marketing
    8.3 Supply Chain Management
    8.4 Operations
    8.5 Finance
    8.6 Others

9 Market, By Deployment Type (Page No. - 57)
    9.1 Introduction
    9.2 Cloud
    9.3 On-Premises

10 Data Monetization Market, By Organization Size (Page No. - 61)
     10.1 Introduction
     10.2 Large Enterprises
     10.3 Small and Medium-Sized Enterprises

11 Market, By Industry Vertical (Page No. - 65)
     11.1 Introduction
     11.2 Banking, Financial Services, and Insurance
     11.3 Telecom
     11.4 Consumer Goods and Retail
     11.5 Media and Entertainment
     11.6 Government and Defense
     11.7 Manufacturing
     11.8 Transportation and Logistics
     11.9 Energy and Utilities
     11.10 Healthcare
     11.11 Others

12 Data Monetization Market, By Region (Page No. - 76)
     12.1 Introduction
     12.2 North America
             12.2.1 United States
             12.2.2 Canada
     12.3 Europe
             12.3.1 United Kingdom
             12.3.2 Germany
             12.3.3 France
             12.3.4 Rest of Europe
     12.4 Asia Pacific
             12.4.1 Australia and New Zealand
             12.4.2 China
             12.4.3 Japan
             12.4.4 Singapore
             12.4.5 Rest of Apac
     12.5 Middle East and Africa
             12.5.1 Kingdom of Saudi Arabia
             12.5.2 United Arab Emirates
             12.5.3 South Africa
             12.5.4 Rest of Mea
     12.6 Latin America
             12.6.1 Brazil
             12.6.2 Mexico
             12.6.3 Rest of Latin America

13 Competitive Landscape (Page No. - 100)
     13.1 Overview
     13.2 Market Ranking
     13.3 Competitive Scenario
             13.3.1 New Product Launches/Upgradations
             13.3.2 Mergers and Acquisitions
             13.3.3 Partnerships, Agreements, and Collaborations

14 Company Profiles (Page No. - 105)
     14.1 Introduction
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
     14.2 1010data
     14.3 Accenture
     14.4 Adastra
     14.5 ALC
     14.6 Cisco
     14.7 Dawex Systems
     14.8 Elevondata
     14.9 Emu Analytics
     14.10 Gemalto
     14.11 Google
     14.12 IBM
     14.13 Iconnectiva
     14.14 Infosys
     14.15 Mahindra Comviva
     14.16 Monetize Solutions
     14.17 Narrative
     14.18 NESS
     14.19 NETSCOUT
     14.20 Openwave Mobility
     14.21 Optiva
     14.22 Paxata
     14.23 Reltio
     14.24 SAP
     14.25 SAS
     14.26 Virtusa

*Details on Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View Might Not Be Captured in Case of Unlisted Companies.

15 Appendix (Page No. - 150)
     15.1 Discussion Guide
     15.2 Knowledge Store: Marketsandmarkets’ Subscription Portal
     15.3 Introduction RT: Real-Time Market Intelligence
     15.4 Available Customizations
     15.5 Related Reports
     15.6 Author Details


List of Tables (79 Tables)

Table 1 Data Monetization Market Size, By Component, 2016–2023 (USD Million)
Table 2 Tools: Market Size By Region, 2016–2023 (USD Million)
Table 3 Services: Market Size By Type, 2016–2023 (USD Million)
Table 4 Consulting Market Size, By Region, 2016–2023 (USD Million)
Table 5 Support and Maintenance Market Size, By Region, 2016–2023 (USD Million)
Table 6 Implementation Market Size, By Region, 2016–2023 (USD Million)
Table 7 Market Size By Data Type, 2016–2023 (USD Million)
Table 8 Customer Data: Market Size By Region, 2016–2023 (USD Million)
Table 9 Product Data: Market Size By Region, 2016–2023 (USD Million)
Table 10 Financial Data: Market Size By Region, 2016–2023 (USD Million)
Table 11 Supplier Data: Market Size By Region, 2016–2023 (USD Million)
Table 12 Data Monetization Market Size, By Business Function, 2016–2023 (USD Million)
Table 13 Sales and Marketing: Market Size By Region, 2016–2023 (USD Million)
Table 14 Supply Chain Management: Market Size By Region,  2016–2023 (USD Million)
Table 15 Operations: Market Size By Region, 2016–2023 (USD Million)
Table 16 Finance: Market Size By Region, 2016–2023 (USD Million)
Table 17 Others: Market Size By Region, 2016–2023 (USD Million)
Table 18 Data Monetization Market, Size By Deployment Type, 2016–2023 (USD Million)
Table 19 Cloud: Market Size By Region, 2016–2023 (USD Million)
Table 20 On-Premises: Market Size By Region, 2016–2023 (USD Million)
Table 21 Market Size By Organization Size, 2016–2023 (USD Million)
Table 22 Large Enterprises: Market Size, By Region, 2016–2023 (USD Million)
Table 23 Small and Medium-Sized Enterprises: Market Size  By Region, 2016–2023 (USD Million)
Table 24 Data Monetization Market Size, By Industry Vertical, 2016–2023 (USD Million)
Table 25 Banking, Financial Services, and Insurance: Market Size By Region, 2016–2023 (USD Million)
Table 26 Telecom: Market Size By Region, 2016–2023 (USD Million)
Table 27 Consumer Goods and Retail: Market Size By Region,  2016–2023 (USD Million)
Table 28 Media and Entertainment: Market Size By Region,  2016–2023 (USD Million)
Table 29 Government and Defense: Market Size By Region,  2016–2023 (USD Million)
Table 30 Manufacturing: Market Size, By Region, 2016–2023 (USD Million)
Table 31 Transportation and Logistics: Market Size By Region, 2016–2023 (USD Million)
Table 32 Energy and Utilities: Market Size By Region, 2016–2023 (USD Million)
Table 33 Healthcare: Market Size By Region, 2016–2023 (USD Million)
Table 34 Others: Market Size By Region, 2016–2023 (USD Million)
Table 35 Data Monetization Market Size, By Region, 2016–2023 (USD Million)
Table 36 North America: Market Size By Country, 2016–2023 (USD Million)
Table 37 North America: Market Size By Component, 2016–2023 (USD Million)
Table 38 North America: Market Size By Service, 2016–2023 (USD Million)
Table 39 North America: Market Size By Data Type, 2016–2023 (USD Million)
Table 40 North America: Market Size By Business Function,  2016–2023 (USD Million)
Table 41 North America: Market Size By Deployment Type,  2016–2023 (USD Million)
Table 42 North America: Market Size By Organization Size,  2016–2023 (USD Million)
Table 43 North America: Market Size By Industry Vertical,  2016–2023 (USD Million)
Table 44 Europe: Data Monetization Market Size, By Country, 2016–2023 (USD Million)
Table 45 Europe: Market Size By Component, 2016–2023 (USD Million)
Table 46 Europe: Market Size By Service, 2016–2023 (USD Million)
Table 47 Europe: Market Size By Data Type, 2016–2023 (USD Million)
Table 48 Europe: Market Size By Business Function, 2016–2023 (USD Million)
Table 49 Europe: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 50 Europe: Market Size By Organization Size, 2016–2023 (USD Million)
Table 51 Europe: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 52 Asia Pacific: Data Monetization Market Size, By Country, 2016–2023 (USD Million)
Table 53 Asia Pacific: Market Size By Component, 2016–2023 (USD Million)
Table 54 Asia Pacific: Market Size By Service, 2016–2023 (USD Million)
Table 55 Asia Pacific: Market Size By Data Type, 2016–2023 (USD Million)
Table 56 Asia Pacific: Market Size By Business Function,  2016–2023 (USD Million)
Table 57 Asia Pacific: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 58 Asia Pacific: Market Size By Organization Size, 2016–2023 (USD Million)
Table 59 Asia Pacific: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 60 Middle East and Africa: Data Monetization Market Size, By Country,  2016–2023 (USD Million)
Table 61 Middle East and Africa: Market Size By Component,  2016–2023 (USD Million)
Table 62 Middle East and Africa: Market Size By Service,  2016–2023 (USD Million)
Table 63 Middle East and Africa: Market Size By Data Type,  2016–2023 (USD Million)
Table 64 Middle East and Africa: Market Size By Business Function, 2016–2023 (USD Million)
Table 65 Middle East and Africa: Market Size By Deployment Type, 2016–2023 (USD Million)
Table 66 Middle East and Africa: Market Size By Organization Size, 2016–2023 (USD Million)
Table 67 Middle East and Africa: Market Size By Industry Vertical, 2016–2023 (USD Million)
Table 68 Latin America: Data Monetization Market Size, By Country, 2016–2023 (USD Million)
Table 69 Latin America: Market Size By Component, 2016–2023 (USD Million)
Table 70 Latin America: Market Size By Service, 2016–2023 (USD Million)
Table 71 Latin America: Market Size By Data Type, 2016–2023 (USD Million)
Table 72 Latin America: Market Size By Business Function,  2016–2023 (USD Million)
Table 73 Latin America: Market Size By Deployment Type,  2016–2023 (USD Million)
Table 74 Latin America: Market Size By Organization Size,  2016–2023 (USD Million)
Table 75 Latin America: Market Size By Industry Vertical,  2016–2023 (USD Million)
Table 76 Market Ranking for the Data Monetization Market, 2018
Table 77 New Product Launches/Upgradations, 2016–2018
Table 78 Mergers and Acquisitions, 2015–2017
Table 79 Partnerships, Agreements, and Collaborations, 2016–2018
 
 
List of Figures (45 Figures)
 
Figure 1 Data Monetization Market Segmentation
Figure 2 Regional Scope
Figure 3 Currency Conversion
Figure 4 Market Research Design
Figure 5 Breakdown of Primary Interviews: By Company, Designation, and Region
Figure 6 Data Triangulation
Figure 7 Market Size Estimation Methodology: Bottom-Up Approach
Figure 8 Market Size Estimation Methodology: Top-Down Approach
Figure 9 Data Monetization Market: Assumptions
Figure 10 Top 3 Segments With the Largest Market Shares in 2018
Figure 11 North America is Estimated to Hold the Largest Market Share in 2018
Figure 12 Increasing Use of External Data Sources is Expected to Be Driving the Growth of the Data Monetization Market During the Forecast Period
Figure 13 Services Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 14 Cloud Deployment Type is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 15 Banking, Financial Services, and Insurance Industry Vertical and North American Region are Expected to Hold the Largest Market Shares
Figure 16 Small and Medium-Sized Enterprises Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 17 Data Monetization Market: Drivers, Restraints, Opportunities, and Challenges
Figure 18 Services Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 19 Financial Data Type is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 20 Sales and Marketing Segment is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 21 Cloud Deployment Type is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 22 Small and Medium-Sized Enterprises Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 23 Telecom Industry Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 24 North America is Expected to Have the Largest Market Size During the Forecast Period
Figure 25 North America: Market Snapshot
Figure 26 Asia Pacific: Market Snapshot
Figure 27 Key Developments By the Leading Players in the Data Monetization Market, 2016–2018
Figure 28 Market Evaluation Framework
Figure 29 Geographic Revenue Mix of Top Market Players
Figure 30 Accenture: Company Snapshot
Figure 31 Accenture: SWOT Analysis
Figure 32 Cisco: Company Snapshot
Figure 33 Gemalto: Company Snapshot
Figure 34 Google: Company Snapshot
Figure 35 IBM: Company Snapshot
Figure 36 IBM: SWOT Analysis
Figure 37 Infosys: Company Snapshot
Figure 38 Infosys: SWOT Analysis
Figure 39 NETSCOUT: Company Snapshot
Figure 40 Optiva: Company Snapshot
Figure 41 SAP: Company Snapshot
Figure 42 SAP: SWOT Analysis
Figure 43 SAS: Company Snapshot
Figure 44 SAS: SWOT Analysis
Figure 45 Virtusa: Company Snapshot 


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Report Code
TC 6282
Published ON
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