Chicago, February 2, 2024 (GLOBE NEWSWIRE) — The Global AI Data Management Market is expected to grow from USD 25.1 billion in 2023 to USD 70.2 billion in 2028, growing at a CAGR of 22.8% during the forecast period, according to a new report by MarketsandMarkets™. The AI data management market is driven by AI-based data structure solutions and automated integration, evolving cloud technology, and rapid advancements in AI and ML to propel adoption of transformative data management solutions.
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AI Data Management Market Dynamics:
Drivers:
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Advances in AI and ML drive market growth
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Sophistication of AI and ML technologies
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Transformative integration in data management
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Reduce manual efforts and minimize errors
Constraints:
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Barriers to Provisioning Comprehensive Datasets
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Inconsistent data quality affects reliability
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Data silos and integration challenges
Opportunities:
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AI enables personalized experiences
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Continuous learning with machine learning
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Strengthen customer relationships
List of Key Players in AI Data Management Market:
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Microsoft (United States)
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AWS (United States)
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IBM (United States)
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Google (United States)
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Oracle (United States)
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Salesforce (United States)
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SAP (Germany)
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SAS Institute (United States)
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HPE (United States)
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Snowflake (United States)
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One of the transformative advancements poised to reshape the AI data management business landscape is the fusion of AI with natural language processing (NLP) and natural language understanding (NLU) capabilities. This integration revolutionizes the way businesses interact with and extract value from their data. Advances in NLP and NLU technologies enable AI systems to understand and interpret human language more effectively. This evolution enables AI-based data management solutions to process unstructured data, such as text, voice and documents, with remarkable accuracy and depth. By understanding the context, semantics and nuances of language, these systems can extract meaningful information from various sources, improving data understanding and analysis. This innovation allows businesses to effortlessly sift through vast volumes of unstructured data, including customer reviews, social media interactions, research papers, and more. AI-based systems equipped with NLP and NLU can derive actionable insights from this unstructured data, complementing structured data sets to provide a comprehensive understanding of market trends, consumer sentiments and emerging opportunities.
The predictive modeling segment of the market is expected to grow at the highest CAGR during the forecast period. Predictive modeling applications in AI data management involve the use of advanced statistical and machine learning techniques to predict future outcomes based on historical and current data patterns. These models analyze large data sets, identifying relationships, trends, and patterns to make predictions or educated guesses about future events or behaviors. By leveraging algorithms such as regression analysis, decision trees, neural networks, and ensemble methods, predictive modeling facilitates various business applications including sales forecasting, risk assessment, demand planning and customer behavior prediction. It enables organizations to anticipate trends, make proactive decisions, optimize resource allocation and mitigate potential risks by harnessing the power of data-driven insights, thereby improving operational efficiency and strategic decision-making process.
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By data type, the image segment is expected to hold the major share in the AI data management market. Image data, characterized by its visual complexity and richness, requires sophisticated AI techniques such as computer vision and deep learning to extract meaningful information. Using convolutional neural networks (CNN) and other deep learning architectures, AI systems can recognize patterns, objects, and features in images, enabling tasks such as image classification , object detection, facial recognition and image segmentation. This technology finds applications in various industries, including healthcare for medical imaging analysis, retail for visual product recognition, autonomous vehicles for scene understanding, and security for surveillance systems. , revolutionizing the way organizations leverage visual data to gain actionable insights and improve decision-making processes.
The AI data management market offers several opportunities ripe for exploration. Players can take advantage of this by focusing on improving AI-driven data processing automation, offering scalable and adaptable solutions that accommodate various data sources and formats. Additionally, it is crucial to capitalize on predictive analytics and machine learning capabilities to predict future trends and provide actionable insights. Focusing on developing AI-driven data governance and security solutions to ensure compliance and protect sensitive information presents another path forward. Additionally, facilitating user-friendly interfaces and democratizing access to AI-driven analytics through intuitive tools will expand the market reach. Players can further explore partnerships with industry-specific experts to tailor AI data management solutions and capitalize on domain-specific requirements, thereby driving innovation and differentiation in a highly competitive market landscape.
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