USD 1.57 Billion
Report ID:
SQMIG45F2089 |
Region:
Global |
Published Date: September, 2024
Pages:
197
|Tables:
144
|Figures:
78
Global Autonomous Data Platform Market size was valued at USD 1.57 Billion in 2022 and is poised to grow from USD 1.93 Billion in 2023 to USD 10.12 billion in 2031, at a CAGR 23.0% during the forecast period (2024-2031).
The market is poised for growth due to the growing adoption of cognitive computing and the advanced analytics technologies. The rapid expansion of social media and connected devices has increased the amount of unstructured data generated by companies. As a result, the demand for autonomous database platforms, especially among SMEs, is expected to increase.
The increasing adoption of cloud platforms in innovation, and the widespread storage of enterprise data in hybrid and public clouds is driving the widespread use of self-contained data platforms in cloud-based environments. Unlike traditional database solutions, autonomous data platforms enable fast, secure analysis, delivery and synthesis of critical data.
Machine learning is used by the autonomous data platform to ensure that it is always running smoothly and in the way that business decision-makers need it to. For instance, machine learning can automatically and continuously patch, upgrade, adapt, and backup the system while it is in use, with little to no operator involvement.
US Autonomous Data Platform Market is poised to grow at sustainable CAGR for the next forecast year
Global Market Size
USD 1.57 Billion
Largest Segment
On-premises
Fastest Growth
Cloud
Growth Rate
al Autonomous Data Platform Market size was valued CAGR
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The global autonomous data platform market is segmented based on component, organization size, deployment, vertical, and region. Based on components, the market is segmented into platform, services, advisory, integration, and support & maintenance. Based on organization size, the market is segmented into small and medium enterprises (SME), and large enterprises. With respect to segmentation by deployment, the market is segmented into on-premises, and cloud. Based on vertical, the market is segmented into BFSI, healthcare and life sciences, retail, manufacturing, telecommunication and media, government, and others. Based on region the global Autonomous Data Platform Market is segmented into North America, Europe, Asia-Pacific, South America, and MEA.
Analysis by Component
As per the global autonomous data platform market forecast, the platform segment accounted for the largest market share of over 68% in 2023, driven by advancing technologies such as digital and cloud-based platforms, along with the rising demand for analytics solutions. Autonomous data tools play a critical role in assessing a company’s big data architecture to tackle key business challenges and ensure optimal database performance. These platforms help organizations enhance and scale their data processing capabilities while providing comprehensive security assessments, including configuration analysis, protection of sensitive data, monitoring of abnormal database activities, and user access control. These factors are expected to propel further growth in the segment.
The services segment is expected to grow at a significant CAGR during the forecast period. The threat of data loss due to malware and the presence of highly sensitive organizational information has heightened the need for robust data protection strategies. To address this challenge, businesses are increasingly adopting data backup and restore platforms, fueling the growth of the database backup and restore services market. The rising demand from large and medium-sized enterprises to securely store, backup, and recover vast volumes of critical data is a key driver of the expansion of this service segment over the forecast period. This trend underscores the growing importance of data security and reliability in today’s digital landscape.
Analysis by Deployment
As per the global autonomous data platform market analysis, the on-premises segment accounted for the largest market share of over 52% in 2023. Organizations that prioritize data privacy and security tend to prefer on-premises installations. These deployments are often seen as more secure than cloud alternatives and offer the flexibility to customize solutions quickly to meet specific business needs, providing greater control over software and infrastructure. By retaining data and IP addresses within their own network, companies minimize the risk of transmitting sensitive information online and reduce dependency on third-party providers for data management and security. These advantages are expected to fuel the growth of the on-premises segment during the forecast period.
The cloud segment is expected to grow at a significant CAGR during the forecast period. The flexibility and cost-effectiveness of cloud-based solutions are driving their growing adoption among users. Cloud computing platforms offer superior scalability, reduced implementation costs, and continuous innovation, making them an attractive choice for businesses. With a virtual environment that allows seamless access to information across interconnected devices anytime, cloud-based solutions simplify service delivery. Instead of storing data locally, users can securely upload and access it via network-connected devices. These advantages of cloud deployment are fueling significant growth in the segment, as more organizations recognize its benefits for efficiency and scalability.
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As per the global autonomous data platform market outlook, North America is dominating. 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. The region has many tech giants such as Intel Corporation, Amazon Web Services, Oracle Corporation, and many others. The region's strong technological infrastructure, combined with a growing need for real-time analytics and compliance with data regulations (such as GDPR and CCPA), creates significant opportunities for market growth.
The autonomous data platform market in Asia Pacific is growing significantly at a CAGR of 27.7% from 2024 to 2031. The region is witnessing tremendous growth driven by rapid technological and digital transformation in emerging economies such as China, India and Southeast Asia. In this region, the rise of the cloud computing and the spread of IoT connectivity are accelerating market expansion. The increasing adoption of AI and machine learning technologies in sectors such as the manufacturing and BFSI is driving demand for the market. Governments in the region are also investing heavily in the smart city initiatives and digital infrastructure, presenting substantial growth opportunities for data management solutions.
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Autonomous Data Platform Market Drivers
Growing Demand for Real-time Analytics
Growing need for real-time data analytics across industries is the key driver of the autonomous data platform market. Autonomous data platforms use artificial intelligence and machine learning to deliver real-time insights through data manipulation, integration and automation. This capability is especially important in industries such as the finance, healthcare and retail, where timely data decisions can significantly impact business and customer satisfaction.
Increasing Adoption of Cloud-based Solutions
The increasing shift towards cloud computing is another important driver of the autonomous data platform market. Cloud-based platforms offer scalability, cost efficiencies and accessibility, making them an attractive solution for businesses of all sizes. Cloud technology is becoming more widely accepted and autonomous data platforms are becoming an important tool for data management easy operation. With the ability to seamlessly integrate with existing IT infrastructure, these platforms provide advanced security and compliance features and reduce data management complexity.
Autonomous Data Platform Market Restraints
High Initial Investment Costs
Despite those advantages, the high initial costs associated with implementing autonomous data platforms act as a significant deterrent. The cost of deployment, as well as the need for skilled staff to initially administer the program, can deter adoption. These constraints may slow the overall market growth, especially in developing communities.
Data Privacy and Security Concerns
Organizations dealing with confidential information such as health records or financial transaction processors are often reluctant to host independent solutions and add complexity. The growing trend of cyberattacks and data breaches raises sensitive information security concerns while these platforms are designed to enhance security measures. Addressing these security concerns is critical to increasing market confidence and encouraging greater adoption. Data privacy and security are key challenges in the autonomous data platform market.
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The autonomous data platform market is characterized by fierce competition between the leading manufacturers, each offering innovative AI-driven solutions. Companies such as Oracle Corporation, IBM, Microsoft and Google are major players in this market, applying their expertise in cloud computing and artificial intelligence. These companies frequently engage in deals and acquisitions to improve their technological capabilities and expand their market reach, meeting the growing demand for scalable, secure and efficient data solutions.
Autonomous Data Platform Market Top Player’s Company Profiles
Autonomous Data Platform Market Recent Developments
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Correlates, and Analyses the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
According to SkyQuest analysis, the global autonomous data platform industry is poised for tremendous growth owing to increasing adoption of advanced cognitive computing and analytics coupled with increasing volume of complex and unstructured data. The market benefits from increasing demand from small and medium-sized enterprises (SMEs) and the rapid adoption of cloud technologies that fuel growth, as enterprises seek to leverage big data to provide customer communication. Key trends include the transition to hybrid cloud and multi-cloud approaches enabling organizations to optimize costs and performance while ensuring data scalability and flexibility. Autonomous data platforms using artificial intelligence (AI) and machine learning (ML) to automate data management systems, including integration, cleaning and inspection thereby reducing manual operations, increasing operational efficiency and reducing errors.
Report Metric | Details |
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Market size value in 2022 | USD 1.57 Billion |
Growth Rate | al Autonomous Data Platform Market size was valued at USD 1.57 Billion in 2022 and is poised to grow from USD 1.93 Billion in 2023 to USD 10.12 billion in 2031, at a CAGR 23.0% |
Base year | 2023 |
Forecast period | 2024-2031 |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Customization scope | Free report customization with purchase. Customization includes:-
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Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the Autonomous Data Platform Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the Autonomous Data Platform Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the Autonomous Data Platform Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the Autonomous Data Platform Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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Report ID: SQMIG45F2089
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