(Wireless-NewsWire.Com, June 18, 2020 ) According to a research report "Autonomous Data Platform Market by Component (Platform and Services), Organization Size (Large Enterprises and Small and Medium-Sized Enterprises), Deployment Type (On-Premises and Cloud), Vertical, and Region - Global Forecast to 2024", published by MarketsandMarkets, estimated to be USD 810 million in 2019, the autonomous data platform market is projected to surpass USD 2,210 million by 2024, registering a CAGR of 22.2% during the forecast period
Browse 57 market data Tables and 29 Figures spread through 126 Pages and in-depth TOC on "Autonomous Data Platform Market - Global Forecast to 2024"
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The growth of this market is driven by the rising adoption of cognitive computing technology and advanced analytics as well as the increasing volume of complex and unstructured data.
The platform segment to hold a higher market share than the services segment during the forecast period
Based on component, the autonomous data platform market has been segmented into platform and services. Between the two components, the platform segment is expected to lead the market during the forecast period.
Enterprises are increasingly adopting autonomous data platforms to effectively and efficiently manage the growing volumes of data in order to enhance productivity and maintain business continuity. Autonomous data platforms not only improve the quality of data-driven insights but also help enterprises enhance their data management capabilities. The proliferation of data has forced data management platform vendors, such as Oracle, MapR, IBM, and AWS, to develop and design autonomous data platforms that help IT teams simplify and manage processes. The autonomous data platform providers are competing with each other to increase their market coverage and expand their presence in newer markets.
Retail vertical to witness the highest CAGR during the forecast period
With the increasing use of the Internet, the retail vertical has become more consumer-centric. Advancements in technologies have also made this vertical witness the rapid changes in consumers’ behavior. Therefore, the autonomous data platform has become an integral part of the retail vertical, helping retailers attain enhanced customer loyalty in the highly competitive market. The platform helps retailers in tracking the customers’ shopping journey in real-time, thus enabling retailers to understand and address their customers’ needs and requirements.
The retail vertical needs a robust autonomous data platform to collect different types of data, including structured and unstructured, from different sources in real-time. The major challenges faced by this vertical include the demand for omnichannel experience and the tracking of consumers in real-time. As autonomous data platforms and services help efficiently address these challenges, their adoption by retailers is expected to increase in the coming years.
Among regions, North America to hold the largest market share during the forecast period
The deep penetration of the Internet and mobile devices in North America has created opportunities for enterprises to reach out to clients, channel partners, and other stakeholders in the region. The extensive use of mobile devices and social media platforms to connect with business partners and customers for delivering customized content as per the business requirements of clients has encouraged organizations to adopt autonomous data platforms and services.
Enterprises focus on offering the best end-user experience and providing the best services by making use of the machine learning technology-based software and services. They leverage the autonomous data platform to analyze customer-related data and to find parameters such as customers buying behavior, seasonal demand, and products demand. With the advent of autonomous data platforms, marketers can centralize customers’ data from different sources at one platform, thereby saving hours of integration work.
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Some of the major vendors in the autonomous data platform market are Oracle (US), Teradata (US), IBM (US), AWS (US), MapR (US), Cloudera (US), Qubole (US), Ataccama (Canada), Gemini Data (US), DvSum (US), Denodo (US), Zaloni (US), Datrium (US), Paxata (US), and Alteryx (US).
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Mr. Aashish Mehra