MLOps Market Size, Share, Growth Analysis, By Infrastructure(Data Infrastructure and Model Infrastructure), By Data Management(Data Pipeline Management and Data Versioning), By Region - Industry Forecast 2024-2031

Report ID: SQMIG45D2064 | Region: Global | Published Date: April, 2024
Pages: 197 | Tables: 59 | Figures: 75

MLOps Market Regional Insights

North America followed by Asia Pacific is one of the leading markers for MLOps in terms of market share. Countries, such as the US and Canada, are adopting ML technology in multiple application areas, propelling the growth of MLOps in this region. In the North American MLOps market, the US is considered one of the major contributors. The presence of prominent technology providers, such as IBM (US), Google (US), Microsoft (US), HPE (US), and AWS (US), is complementing the growth of the market in this region. The presence of such established MLOps companies and the emergence of new start-ups will strengthen the outlook of this region and enable it to witness a significant increase in investments and early adoption of Artificial Intelligence technology.

MLOps Market Report Snapshots

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Global MLOps Market size was valued at USD 1.10 billion in 2022 and is poised to grow from USD 1.55 billion in 2023 to USD 24.23 billion by 2031, growing at a CAGR of 41% during the forecast period (2024-2031).

The global MLOps market is characterized by a mix of established companies and emerging players. Market participants are focusing on research and development activities to enhance the efficiency and performance of MLOpss. Additionally, strategic collaborations, partnerships, and mergers and acquisitions are prevalent strategies adopted by companies to expand their market presence. The competitive environment is further influenced by factors such as technological advancements, government regulations, and the ability to provide cost-effective and sustainable solutions. 'IBM (US)', 'Microsoft (US)', 'Google (US)', 'AWS (US)', 'HE (US)', 'GAVS Technologies (US)', 'DataRobot (US)', 'Cloudera (US)', 'Altery (US)', 'Domino Data Lab (US)', 'Valohai (US)', 'H20.ai (US)', 'MLflow (Netherlands)', 'Neptune. ai (Europe)', 'Comet (US)', 'SparkCognition (US)', 'Hopsworks (Europe)', 'Datatron (US)', 'Weights & Biases (US)', 'Katonic.ai (Australia)'

Manual data reprocessing and collecting are ineffective and might produce unsatisfactory results. MLOps helps for automating the whole ML model workflow. This includes data gathering, model construction, testing, retraining, and development. MLOps help companies save time and reduce error rates. Collaboration is seen between IT and business personnel, as well as data scientists and engineers, for the company-wide adoption of ML models. Businesses can standardize ML operations and establish a standardized language for all participants due to MLOps principles. This reduces compatibility problems and quickens the construction and deployment of modelling processes.

Few key market trends in the global MLOps market are MLOps platforms incorporating more automation features, such as auto-model selection and auto-tuning. This is helping businesses to reduce the time and cost of model development. Many MLOps platforms are cloud-based, as they offer scalability and flexibility to businesses. Cloud providers are also offering more machine learning services, such as automatic model deployment and monitoring. Collaboration between data scientists and IT operations teams is key to effective MLOps. Platforms are incorporating collaboration features to facilitate this. As machine learning models become more complex, it is becoming increasingly important to understand how they make decisions. Explainable AI is a trend in MLOps that aims to provide insight into why machine learning models make certain decisions. As more sensitive data is being used in machine learning models, ensuring security is crucial. MLOps platforms are incorporating security features to protect sensitive data and prevent cyber attacks.

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MLOps Market Size, Share, Growth Analysis, By Infrastructure(Data Infrastructure and Model Infrastructure), By Data Management(Data Pipeline Management and Data Versioning), By Region - Industry Forecast 2024-2031

MLOps Market Regional Insights

MLOps Market Report Snapshots

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