Hadoop & Big Data Analytics Market Is Expected USD 23.5 billion by 2025

 


Various factors such as the growing emphasis on digital transformation, an increase in analytics investments, an increased emphasis on remote monitoring in support of the COVID-19 pandemic, the growing adoption of smart payment technologies, and the business needs to build a digital infrastructure for large-scale deployments are expected to drive the adoption of Hadoop big data analytics.

The Hadoop & big data analytics market is expected to slow in 2020 as a result of COVID-19-related lockdowns around the world. Global manufacturing, retail and eCommerce, government, and public sectors have all been affected by these lockdowns. They have also had an impact on supply chains and logistics as a result of the complete or partial halting of operations in various verticals. The worst-affected industries include manufacturing, transportation and logistics, retail and eCommerce, and so on. The condition is expected to be under control by early 2021, while demand for Hadoop big data analytics solutions and services are expected to rise due to increased demand for remote health monitoring of individuals and assets, sales and customer management, predictive asset maintenance, and predictive asset management.

Businesses across multiple industries are already planning to deploy a wide range of Hadoop big data analytics solutions to carry out the digital transformation of mission-critical processes, which is expected to improve operations and strengthen customer relationships.

The key business and operational priorities of enterprises that are expected to drive the adoption of Hadoop big data analytics solutions worldwide is the reduction of infrastructure and operational costs, improvement of customer experiences, enhancement of data security and privacy, increase in operational visibility for various processes, and improvement in real-time business decision-making.

The global Hadoop & big data analytics market is expected to grow from USD 12.8 billion in 2020 to USD 23.5 billion by 2025, at a CAGR of 13.0 percent over the forecast period.

Contactless and smart payments are inextricably linked. While contactless payments make it easier to transfer money between multiple parties, IoT automates and connects various processes and tasks. Contactless payments are increasingly being made with devices other than contactless cards, such as key fobs and wearables.

A large number of digital firms are utilizing machine learning to gather insights from the field of commerce. Public transportation systems have also evolved, moving away from cash and paper-based transactions and toward electronic payment methods. The adoption of smart payment technologies has increased as a result of the COVID-19 situation, which has resulted in social distancing. The increase in COVID-19 cases has also accelerated the adoption of contactless payments. During this pandemic, governments are advising their citizens to use digital and contactless modes of payment because the transfer of physical currency could lead to an increase in the number of Covid-19

The Hadoop big data analytics market is classified according to business function. Marketing and sales, operations, human resources, and finance are examples of business functions. Many global operations teams have access to enough real-time shop-floor data and the expertise to conduct such sophisticated statistical valuations. Using Hadoop big data analytics, operational teams can identify inefficiencies in their workflows and, as a result, change their processes to streamline operations.

North America is expected to have the largest market share in the global Hadoop big data analytics market, with Asia Pacific (APAC) growing at the fastest CAGR during the forecast period. Some of the major factors driving the growth of the Hadoop's big data analytics market in APAC is the increasing volume of data, advancements in AI and big data technologies, growing concern about data integrity, and increasing demand for useful insights. China, India, and Japan are particularly focused on improving data management to enable data-driven business decisions and improve business performance.

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