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An autonomous data platform is an infrastructure for Big Data that operates and optimizes the data by itself. By observing the user's actions, such as which data tables are being used, the number of data clusters being built, and the efficiency of using those clusters, it learns how to handle and manage the data independently.
It is an automated cloud database application that enhances analytic workloads, including data marts, data lakes, and workloads. Business analysts and data scientists can easily measure business understandings of any type or size of data cost-effectively.
Technological advancements such as cognitive computing, data analytics, and rising demand for cloud-based solutions are driving the autonomous data platform in the coming years. Prioritization of network paradigms and introduction to actionable intelligence to reduce data loss are some additional factors for market growth. Moreover, the introduction of expandable, complex, and unstructured data hinders the development of autonomous data platforms.
An autonomous data platform offers flexibility to organizations enabling them to work as per convenience and requirements. An autonomous data platform provides easy and quick ways to distribute, measure, and integrate critical data.
The COVID-19 pandemic has accelerated the growth of digitization, demand for remote services, location data, investments in data analytics, and real-time tracking.
The pandemic increased businesses' reliance on cloud-based services to process, analyze and share data with remote employees, benefiting the autonomous data platform. Thus, there was an increase in the use of autonomous data platforms due to rise in autonomous operations, permission to network rights, and advanced analytical tools by organizations.
Moreover, many organizations had to move their client services completely or partially to virtual mode, which eventually helped develop the information technology departments of these organizations.
The report will cover the following key insights:
The cloud segment accounts for the large revenue share in the autonomous data platform market. The effectiveness and flexibility of cloud-based solutions make them a better choice for users to adopt. It also offers enhanced scalability, lower operation costs, and enduring developments. The virtual environment allows organizations to access data over interconnected devices according to their convenient time. Users can upload the data by connecting over the network instead of storing it on local devices.
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The global market is analyzed across North America, the Middle East and Africa, South America, Asia Pacific, and Europe.
The North America region holds the major revenue share in the autonomous data platform market due to rapid digitization of businesses and higher penetration of internet and mobile devices, creating opportunities for organizations to connect with the client, channel partners, and other stakeholders. The region has many tech giants such as Intel Corporation, Amazon Web Services, Oracle Corporation, and many others.
Intel finds value in Big Data as the firm uses it to develop chips faster, recognizing glitches and security issues. The firm eases predictive analysis and has invested over USD 200 million in Big Data developments. The White House has also financed over USD 200 million in Big Data developments.
The distribution of the autonomous data platform market by region is as follows:
The report includes key players such as Oracle, IBM, Teradata, Amazon Web Services, Inc., Cloudera, Inc., Hewlett Packard Enterprise Development LP, Qubole, Gemini Data, Alteryx, Inc., Denodo Technologies, Denodo, MapR, Ataccama, Zaloni, Datrium, Qubole, DvSum, and many others.
By Organization Size
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