The Data Monetization Market is a synopsis to the study of ICT industry and the report also provides valuable insights about the leading drivers, upcoming trends, applications and challenges, determined by our Experts. SWOT analysis is the method to tell any market’s strengths and weaknesses (i.e. drivers and restrains) so that you know on what to stick and what to avoid, this report not only consists SWOT analysis but also provides with the CAGR value fluctuation on the Forecast period of 2018-2025. The various advantages offered by the Data Monetization Market is driving the growth of the market. Our research analysts have identified the technological advancements and features as one of the primary factors that will trigger the growth of the Data Monetization Market in the coming years.
According to the report, global demand for Data Monetization market was valued at approximately USD 1.3 billion in 2017 and is expected to reach around at a CAGR of 17.6% between 2018 and 2025.
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The Data Monetization market is highly fragmented and is based on new product launches and clinical results of products. Hence the major players have used various strategies such as new product launches, clinical trials, markett initiatives, high expense on research and development, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market. The report includes market shares of Data Monetization market for global, Europe, North America, Asia Pacific and South America.
Data monetization is the way towards changing the substantial unstructured volume of big business information into profitable bits of knowledge for drawing financial esteem or trade of administration. It involves the utilization of information resources that generate value to the organizations. Data monetization can be done in two ways: by directly and by indirectly. The huge amount of information created can be bundled into information items and sold (direct monetization) or it can be processed to extract insights (indirect monetization) and can be utilized to help business choices.
Data Monetization may assist associations with reducing information stockpiling expenses or increment income by putting resources into investigation stage which changes over unstructured information into significant bits of knowledge in view of the necessities. Data monetization refers to the procedure of prioritizing the asset value in order to create high income. It is the way to change the unstructured vast volume of information in profitable bits of knowledge and transforming the information into money or mode of trade administration. The purpose of data monetization is to sort the unstructured information in a crude manner, store the information in data frameworks and discharge the structured data across every vertical in an organization. Moreover it causes associations to build income by putting resources into examination stage, which acquires important bits of knowledge from the unstructured information. The recent trends in data monetization includes emergence of cloud storage and cloud computing which helps many organizations to secure their data with security protocols.
The well players in data monetization market
Adastra Group, CellOS Software Ltd, Connectiva Analytics and Insights Ltd., Dawex Systems, Infosys Limited, Mahindra ComViva, Mnubo, Netscout Systems, Inc, Virtusa Corporation, Infosys, Google, IBM, Cisco, 101 data, Accenture, Monetize Solutions, Narrative, NESS, NETSCOUT,Paxata, Inc., Optiva Inc., (Redknee Solutions Inc.), ALC, SAP SE, SQLstream, Inc., Openwave Mobility among others.
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Market segment on basis of Regions/Countries Regions/Countries
- North America & South America,
- Asia-Pacific, and
- Middle East & Africa.
Some of the major countries covered in this report are U.S., Canada, Germany, France, U.K., Netherlands, Switzerland, Turkey, Russia, China, India, South Korea, Japan, Australia, Singapore, Saudi Arabia, South Africa, and Brazil among others. In 2017, North America is expected to dominate the market.
Based on component, the global data monetization market is segmented into
- tools and
The services segment can further be sub segmented into support and maintenance, consulting and implementation.
Based on data type, the market can be segmented into
- customer data,
- product data,
- financial data and supplier data
Based on business segments, the market can be segmented into
- sales and marketing,
- supply chain management,
- finance and others (R&D, HR, and legal)
Based on deployment model, the market can be segmented into
- cloud and
- On premises.
Based on organization size, the market can be segmented into small and medium-sized enterprises (SMES) and large enterprises.
Based on industry vertical, the market can be segmented into 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 and others (real estate, education, and travel and hospitality).
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Scope of Report:
- Precise estimation of the global Data Monetization market size, share and its contribution to the Global Data Monetization market
- Accurate predictions on upcoming trends and changes in consumer behavior
- Growth of the Data Monetization industry across various geographies such as the North America Europe, Asia-Pacific, South America and Middle East & Africa.
- A thorough analysis of the market’s competitive landscape and detailed information on several vendors
- Detailed information on factors that will accelerate the growth of the Data Monetization market in upcoming years
- Comprehensive information about factors that will challenge the growth of Data Monetization manufacturers
Major market drivers and restraints
- Rapid adoption of advanced analytics and visualization.
- The varying structure of regulatory policies.
- Improper implementation of security protocols may cause data and security theft.
- Increasing use of external data sources.
- Increasing adoption of data-driven decision-making.
- Increasing volume and variety of business data.
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