Press release
Worldwide Analysis on Data Analytics Outsourcing Market Strategies and Forecasts, 2016 to 2024
India being the biggest hub of data analytics is looking to stay ahead of President Trump’s H-1B work-visa changes by lobbying the U.S. lawmakers and considering to train American professionals for tasks that Indians can perform excellently. Trump’s pledge of bringing back jobs to the blue-collar areas struggling in the U.S. is prophesied to be supported by Indian IT firms wanting to keep out of the crosshairs of his administration. National Association of Software and Services Companies (Nasscom) is planning to collaborate with the U.S. universities and invest in new trade schools to address the skills shortage in the country. Moreover, recently, Prime Minister Modi had a discussion in New Delhi with 26 U.S. delegates where he emphasized the significance of skilled Indian talent for the U.S. economy.
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The global data analytics outsourcing market could be segmented according to key parameters such as vertical, application, and type. The heart of data analytics is the deciphering of business data to make processes profitable and streamlined and leveraging decision-making ability through actionable insights.
The report put up by our expert analysts includes the top insights of the global data analytics outsourcing market which unveil the future outlook as well as the current trends of the industry. It is a collection of precise guidelines to ensure a tangible success in the market.
Global Data Analytics Outsourcing Market: Trends and Opportunities
In the recent time, the world market for data analytics outsourcing has been witnessing a strong momentum on the part of cloud-based business analytics. Notwithstanding, analytics from social media platforms, fraud analytics in the BFSI domain, cyber analytics and cyber risk management, and customer analytics have emerged as weighty trends in the data analytics outsourcing market.
It is expected of effective data analytics services to win a significant boost in demand as a result of the scarce availability of analysts capable of formulating competitively favorable data insights. Businesses from different sectors have come in line with the unparalleled advantages of using competent data analytics for the purpose of magnifying revenue potential and thoroughly understanding customer choices. Howbeit, not all businesses have the experience to efficiently analyze data and access to in-house resources and knowledge required. This is expected to remarkably augment the demand in the global data analytics outsourcing market.
Global Data Analytics Outsourcing Market: Geographical Analysis
The international data analytics outsourcing market is anticipated to be ruled over by India, owing to the latest advancements in telecommunications and technology. Such developments have elevated the potential of the India data analytics outsourcing market. More than 50.0% of the data analytics projects in the world are outsourced to India on account of excessive availability of adroit labor force specializing in contextual domain analytics.
Other reasons predicted to help Asia Pacific gain an upper hand in the market include cheaper labor costs and systematized technology and telecom infrastructure. The presence of seasoned BPOs in Asia Pacific, especially in India, could also be accredited for the towering growth of the regional market.
Nonetheless, Western Europe and North America are envisaged to produce a large measure of demand for data analytics outsourcing. The Eastern Europe and LAMEA data analytics outsourcing markets are projected to exhibit a quick growth in the near future.
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Global Data Analytics Outsourcing Market: Competitive Overview
The worldwide data analytics outsourcing market houses a host of players mastering in end-to-end data analytics solutions that are peculiar to a thousand and one domains. Out of the pre-eminent companies setting their influence on the market, Infosys Ltd., Citigroup Inc., Capgemini S.A., Tata Consultancy Services Ltd., and Cognizant are envisioned to stay dominant.
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