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Machine Learning Model Operationalization Management Market Analysis 2024 -2033: Forecasted Market Size, Top Segments, And Largest Region | Amazon.com Inc., Google LLC, Microsoft Corporation, Dataiku, Azure Machine, IBM Corporation, Hewlett-Packard enterp
The Business Research Company has updated its global market reports, featuring the latest data for 2024 and projections up to 2142The Business Research Company offers in-depth market insights through Machine Learning Model Operationalization Management Global Market Report 2024, providing businesses with a competitive advantage by thoroughly analyzing the market structure, including estimates for numerous segments and sub-segments.
Market Size And Growth Forecast:
The machine learning model operationalization management market size has grown exponentially in recent years. It will grow from $1.31 billion in 2023 to $1.92 billion in 2024 at a compound annual growth rate (CAGR) of 46.7%. The growth in the historic period can be attributed to increasing adoption rate of machine learning, growing adoption of machine learning (ML), rising complexity of models, increased data volumes, and rise of edge computing.The machine learning model operationalization management market size is expected to see exponential growth in the next few years. It will grow to $7.85 billion in 2028 at a compound annual growth rate (CAGR) of 42.1%. The growth in the forecast period can be attributed to demand for automation, focus on model governance and compliance, integration with DevOps practices, focus on cost optimization, and increased investment in AI infrastructure. Major trends in the forecast period include automated model deployment, technological advancements and AutoML advancements.
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Market Segmentation:
The machine learning model operationalization management market covered in this report is segmented -
1) By Component: Platform, Services
2) By Deployment Mode: Cloud, On-premise
3) By Organization Size: Large Enterprises, Small And Medium Enterprises (SMEs)
4) By End User: Banking, Financial Services And Insurance (BFSI), Manufacturing, Information Technology (IT) And Telecom, Healthcare, Media And Entertainment
Major Driver - Rising Demand For Real-Time Decision-Making A Catalyst For Growth In The Machine Learning Model Operationalization Management Market
The increasing demand for decision-making is expected to propel the growth of the machine learning model operationalization management market going forward. Decision-making refers to the ability to make informed decisions quickly by utilizing up-to-the-minute data and analytics. Machine learning model operationalization management (MLOps) helps in real-time decision-making by enabling the efficient deployment, monitoring, and management of machine learning models in production environments. For instance, in September 2022, according to a report by CIO, a US-based magazine related to technology and IT, around 88% of IT decision-makers agreed that data collection and analysis have the potential, and 84% of organizations have already deployed or have data-driven projects on their roadmaps. Therefore, demand for decision-making is driving the growth of the machine learning model operationalization management market.
Competitive Landscape:
Major companies operating in the machine learning model operationalization management market report are Amazon.com Inc., Google LLC, Microsoft Corporation, Dataiku, Azure Machine, IBM Corporation, Hewlett-Packard enterprise Company, Databricks Inc., Alteryx Inc., Aporia, Cloudera Inc., DataRobot Inc., Fractal Analytics Inc., Domino Data Lab Inc., Seldon Technologies Limited, Iguazio, NeptuneLabs GmbH, Saturn Cloud Inc., H2O.ai Inc., ModelOp, Algorithmia, SAS Model Manager, SAS Viya
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Top Trend - Innovative Advancements In Machine Learning Operationalization A Focus On AutoML Solutions
Major companies operating in the machine learning model operationalization management market are developing innovative products, such as AutoML tools, to make machine learning more accessible, efficient, and scalable for organizations. AutoML (Automated Machine Learning) tools refer to software platforms or frameworks that automate the process of building and deploying machine learning models. For instance, in May 2021, Google Cloud, a US-based provider of cloud computing services, launched Vertex AI, a managed machine learning (ML) platform that allows companies to accelerate the deployment and maintenance of artificial intelligence (AI) models. Vertex AI's AutoML eliminates the need for extensive machine learning expertise, and it automates many of the processes involved in building and fine-tuning machine learning models. It provides tools for data preparation, model training, and deployment.
The Table Of Content For The Market Report Include:
1. Executive Summary
2. Machine Learning Model Operationalization Management Market Characteristics
3. Machine Learning Model Operationalization Management Market Trends And Strategies
4. Machine Learning Model Operationalization Management Market - Macro Economic Scenario
5. Machine Learning Model Operationalization Management Market Size And Growth
…..
27. Machine Learning Model Operationalization Management Market Competitor Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
30. Appendix
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