Cloud Machine Learning Operations (MLOPS) Market
Insightace Analytic Pvt. Ltd. has released the release of the Market Assessment Report for the Global Cloud Machine Learning Operations (MLOPS) Market (Types (Platforms, Services), Applications (BFSI, Healthcare, Retail, Manufacturing, Public Sector, Other), Trends, Industry Competitive Analysis, Forecasts through 2031.
According to a latest survey by Insightace Analytic, the Global Cloud Machine Learning Operations (MLOPS) market is valued at US$1.99 billion in 2023, and is expected to reach US$3,156.0 million by 2031, with a CAGR of 42.3% during the 2024-2031 forecast period.
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MLOPS, short for machine learning operations, refers to a set of best practices that enable organizations to effectively manage and operate artificial intelligence (AI) initiatives, particularly using cloud-based services and software tools. Located at the intersection of DevOps and machine learning, MLOPS aims to promote the continuous development, deployment and maintenance of machine learning models within production environments, ensuring reliability, efficiency, and scalability.
One of the key trends shaping the MLOPS landscape is the expansion of adoption of cloud-based MLOPS platforms. These cloud-native solutions offer greater benefits over traditional on-premises deployments, including increased security, faster implementation schedules, improved scalability, and cost-effectiveness. Organizations that leverage cloud platforms such as IBM Cloud, Alibaba Cloud, Google Cloud Platform (GCP), Microsoft Azure, and Amazon Web Services (AWS) also benefit from the technical expertise and robust infrastructure of these service providers.
However, ensuring the accuracy and performance of models deployed during production remains a challenge, especially when raw data is used to generate predictions and to derive results. Continuous evaluation and retraining is essential, but manually labeling new data labels is time consuming and inefficient. As a result, organizations should carefully assess whether to apply a monitored learning approach, an unsupervised learning approach, or to use existing models to automate labeling of incoming data. Methodology choice depends on the specific nature of the task and the comprehensive business goals.
A list of prominent players in the Cloud Machine Learning Operations (MLOPS) market:
•IBM
•Datarobot SAS
Microsoft
•Amazon
• Google
•dataiku
•DataBricks
•HPE
•Lguazio
•ClearMl
Modzy
•comet
•Cloudera
•Paper Pace
Varrohai
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Market dynamics
driver:
The growth of the MLOPS market is driven primarily by the increased complexity and diversity of machine learning models. Modern machine learning systems now incorporate a wide range of architectures, algorithms, parameters, data input and output, performance metrics, and application usage cases. All of these contribute to the model's refinement. As a result, there is a growing demand for sophisticated tools and methodologies to manage the complete lifecycle of these models, including development, deployment and ongoing maintenance. The MLOPS platform addresses these needs by enabling organizations to standardize workflows between teams and projects, and automates critical processes such as data pre-processing, model deployment, and performance monitoring. These platforms also provide feedback mechanisms to support continuous model optimization, ultimately increasing the overall efficiency and effectiveness of machine learning operations.
assignment:
One of the major challenges facing the MLOPS market is the lack of standardization and interoperability between the various platforms and services available. A wide range of providers are classified, each with their own architecture, implementation style and operational methodology, including MLOPS solutions from startups, software companies and cloud service vendors of Far. This fragmentation causes significant differences in the capabilities, user interfaces and integration capabilities between platforms, hindering seamless adoption and cross-platform compatibility. The lack of unified standards creates barriers for organizations seeking to deploy consistent, scalable MLOPS strategies.
Regional Trends:
North America is currently leading the global MLOPS market in terms of revenue and is expected to maintain a high combined annual growth rate (CAGR) over the next few years. The region is home to major industry players such as IBM, Databricks, Google, Microsoft, and Amazon Web Services (AWS), all of which offer a wide range of MLOP platforms tailored to the diverse requirements of the industry. These companies also invest heavily in research and development, further encouraging innovation and market expansion. Meanwhile, the Asia-Pacific region is emerging as a rapidly growing market, driven by increased investment in AI and machine learning technologies. Regions that focus on general data protection regulations (GDPR) and similar policies, particularly in data privacy and regulatory compliance, are shaping the demand for responsible MLOPS solutions. This evolving regulatory environment has contributed to accelerate adoption of highly secure, compliant MLOPS platforms across the Asia-Pacific region.
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Recent developments:
•In May 2023, the new AI and data platform, IBM Watsonx, was announced at the annual Think Conference. The platform allows businesses to use reliable data to expand and accelerate the effectiveness of their most sophisticated AI. Companies currently employing AI need access to a comprehensive technology stack that allows them to train, coordinate and deploy AI models, including basic models and machine learning capabilities, across organizations with reliable data, speed and governance. This stack is available in a single location and can work in a cloud environment.
Cloud Machine Learning Operations (MLOPS) Market Segmentation –
Depending on the type –
Platform
•service
By application –
•BFSI
• health care
• retail
• Manufacturing
Public Sector
•others
By region –
North America-
•US
•Canada
•Mexico
Europe-
•Germany
UK
•France
•Italy
•Spain
Remains of Europe
Asia Pacific –
• China
• Japan
•India
•South Korea
•Southeast Asia
Remains of Asia Pacific Region
latin america-
•Brazil
•Argentina
Latin America Remains
Middle East and Africa –
•GCC countries
•South Africa
Remains of the Middle East and Africa
Read the summary report – https://www.insightaceanalytic.com/report/cloud-machine-learning-operations-mlops-market/2841
About Us:
Insightace Analytic is a market research and consulting company that enables clients to make strategic decisions. Our qualitative and quantitative market intelligence solutions inform you of the need for market and competitive intelligence and expanding your business. We help our clients identify untapped markets, explore new and competing technologies, segment potential markets, and relocate products to gain a competitive advantage. Our expertise is to provide in-depth analysis with key market insights in a timely and cost-effective way to intelligent reports for syndicated and custom markets.
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This release has been published on OpenPR.
