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World Autonomous Data Platform Market Outlook, 2024 - Growing Demand from SMEs & Increasing Adoption of Cloud Technology Presents Lucrative Opportunities

Dublin, Nov. 08, 2019 (GLOBE NEWSWIRE) -- The "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" report has been added to ResearchAndMarkets.com's offering.

The global autonomous data platform market is expected to grow from US$810 million in 2019 to US$2.21 billion by 2024, at a CAGR of 22.2%.
The rise in adoption of cognitive computing technology and advanced analytics, increasing volume of unstructured data (due to the phenomenal growth of interconnected devices and social media), and increasing volume of complex data are the major factors driving the growth of the autonomous data platform market.The autonomous data platform market includes various major vendors, such as 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).By component, the platform segment expected to hold a higher market share than the services segment during the forecast period

Increasing demand amongst enterprises to handle complex data formats is expected to draw the demand for autonomous data platforms. Enterprises are 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 the autonomous data platform vendors, such as Oracle, MapR, IBM, and AWS, to develop and design autonomous data platforms to help IT teams simplify and manage processes.

Cloud-based deployment expected to have significant growth during the forecast period

Scalability, enhanced collaboration, and cost-effectiveness offered by the cloud platform are expected to boost the demand for cloud-based autonomous data platforms. Enterprises are looking forward to having their solution deployed on the cloud, as the cloud deployment offers various advantages, such as scalability, flexibility in capacity, and enhanced collaboration. The cloud-based autonomous data platform delivers benefits such as reduced cost, as enterprises do not need to build and manage the infrastructure; all the required infrastructure is provided and managed by third parties (CSPs), leading to a reduced upfront cost.The implementation of cloud-based autonomous data platforms enables SMEs and large enterprises to focus on their core competencies, rather than IT processes. The cloud-based data management platform offers a centralized way to integrate the system and its components with web and mobile applications, thus helping organizations boost their efficiency. As a result, a majority of organizations are switching to cloud-based autonomous data platforms. Security concerns remain a critical issue that restricts cloud adoption. However, the security issues are gradually being eliminated through rigorous security tests of the highest standards by third parties.

North America expected to have the largest market size during the forecast period

The extensive use of mobile devices and social media platforms to connect with business partners and customers for delivering customized content as per business requirements of clients has encouraged organizations to adopt autonomous data platforms and services in North America. Autonomous data platforms are marketer-managed systems that provide unified and persistent customer profiles, which are used for segmentation and marketing automation across channels. 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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