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세계의 머신러닝 모델 운영 관리 시장 보고서(2024년)
Machine Learning Model Operationalization Management Global Market Report 2024
상품코드 : 1458686
리서치사 : The Business Research Company
발행일 : On Demand Report
페이지 정보 : 영문 175 Pages
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한글목차

머신러닝 모델 운영 관리 시장 규모는 향후 몇 년동안 연평균 성장률(CAGR) 42.1%로 2028년 78억 5,000만 달러에 달할 것으로 예상됩니다. 이러한 성장 전망은 자동화 수요 증가, 모델 거버넌스 및 규정 준수에 대한 집중, DevOps 관행과의 통합, 비용 최적화에 대한 관심 증가, AI 인프라에 대한 투자 증가 등 여러 가지 요인에 기인합니다. 이 기간 동안 예상되는 주요 동향으로는 모델 자동 배포, 기술 발전, 자동 머신러닝(AutoML) 관행의 발전 등이 있습니다.

의사결정에 대한 수요 증가는 향후 머신러닝 모델 운영 관리 시장의 성장을 견인할 것으로 예상됩니다. 의사결정에는 최신 데이터와 분석을 활용하여 정보에 입각한 신속한 의사결정을 내리는 것이 포함됩니다. 머신러닝 모델 운영 관리(MLOps)는 프로덕션 환경에서 머신러닝 모델을 효율적으로 도입, 모니터링, 관리할 수 있도록 함으로써 실시간 의사결정을 촉진합니다. 예를 들어, 2022년 9월 미국 기술 및 IT 전문지 CIO의 보고서에 따르면, IT 의사결정권자의 약 88%가 데이터 수집 및 분석의 잠재력을 인정하고 있으며, 84%의 조직이 데이터 기반 프로젝트를 진행 중이거나 계획하고 있다고 합니다. 따라서 의사결정에 대한 수요가 머신러닝 모델 운영 관리 시장의 성장을 견인하고 있습니다.

머신러닝 모델 운영 관리 시장의 주요 기업들은 AutoML 툴을 포함한 혁신적인 제품 개발에 주력하고 있으며, AutoML(자동 머신러닝) 툴은 머신러닝 모델 구축 및 배포 프로세스를 자동화하여 조직에서 머신러닝을 보다 쉽고, 효율적이며, 확장 가능하게 만들어 줍니다. 자동화합니다. 예를 들어, 2021년 5월 구글 클라우드는 기업이 인공지능(AI) 모델의 배포와 유지보수를 가속화할 수 있는 관리형 머신러닝(ML) 플랫폼인 버텍스 AI(Vertex AI)를 발표했는데, 버텍스 AI의 AutoML은 광범위한 머신러닝 전문 지식이 필요하지 않고, 머신러닝 모델 구축과 미세 조정이 가능하다, 머신러닝 모델 구축 및 미세 조정과 관련된 많은 프로세스를 자동화합니다. 데이터 준비, 모델 훈련 및 배포를 위한 도구를 제공합니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향과 전략

제4장 거시경제 시나리오

제5장 세계 시장 규모와 성장

제6장 시장 세분화

제7장 지역 및 국가별 분석

제8장 아시아태평양 시장

제9장 중국 시장

제10장 인도 시장

제11장 일본 시장

제12장 호주 시장

제13장 인도네시아 시장

제14장 한국 시장

제15장 서유럽 시장

제16장 영국 시장

제17장 독일 시장

제18장 프랑스 시장

제19장 이탈리아 시장

제20장 스페인 시장

제21장 동유럽 시장

제22장 러시아 시장

제23장 북미 시장

제24장 미국 시장

제25장 캐나다 시장

제26장 남미 시장

제27장 브라질 시장

제28장 중동 시장

제29장 아프리카 시장

제30장 경쟁 구도와 기업 개요

제31장 기타 주요 기업 및 혁신 기업

제32장 경쟁 벤치마킹

제33장 경쟁 대시보드

제34장 주요 인수합병(M&A)

제35장 향후 전망과 가능성 분석

제36장 부록

LSH
영문 목차

영문목차

Machine learning model operationalization management involves preparing a machine learning model for deployment and integration into business applications, analytical platforms, or other operational environments. It aims to streamline the analytics development life cycle and enhance model stability by automating repetitive workflow steps.

The primary components of machine learning model operationalization management are platforms and services. A platform for managing the operationalization of machine learning models is a software platform that enables organizations to efficiently deploy, manage, and monitor machine learning models in production environments. These platforms can be deployed in cloud-based or on-premise modes and cater to organizations of various sizes, including large enterprises and small and medium enterprises (SMEs). They find application in industries such as banking, financial services and insurance (BFSI), manufacturing, information technology (IT) and telecom, healthcare, and media and entertainment.

The machine learning model operationalization management market research report is one of a series of new reports from The Business Research Company that provides machine learning model operationalization management market statistics, including machine learning model operationalization management industry global market size, regional shares, competitors with a machine learning model operationalization management market share, detailed machine learning model operationalization management market segments, market trends and opportunities, and any further data you may need to thrive in the machine learning model operationalization management industry. This machine learning model operationalization management market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

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 the increasing adoption rate of machine learning, growing adoption of machine learning (ML), rising complexity of models, increased data volumes, and the 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 forecasted growth in the upcoming period can be attributed to several factors, including the increasing demand for automation, a focus on model governance and compliance, integration with DevOps practices, a heightened focus on cost optimization, and increased investment in AI infrastructure. Major trends expected during this period include automated model deployment, technological advancements, and advancements in Automated Machine Learning (AutoML) practices.

The increasing demand for decision-making is expected to drive the growth of the machine learning model operationalization management market in the future. Decision-making involves making informed decisions quickly by utilizing up-to-date data and analytics. Machine learning model operationalization management (MLOps) facilitates real-time decision-making by enabling efficient deployment, monitoring, and management of machine learning models in production environments. For example, in September 2022, a report by CIO, a US-based technology and IT magazine, indicated that approximately 88% of IT decision-makers acknowledged the potential of data collection and analysis, and 84% of organizations have either deployed or planned data-driven projects. Hence, the demand for decision-making is fueling the growth of the machine learning model operationalization management market.

Major companies in the machine learning model operationalization management market are focusing on developing innovative products, including AutoML tools, to make machine learning more accessible, efficient, and scalable for organizations. AutoML (Automated Machine Learning) tools automate the process of building and deploying machine learning models. For example, in May 2021, Google Cloud launched Vertex AI, a managed machine learning (ML) platform that enables 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 automates many processes involved in building and fine-tuning machine learning models. It provides tools for data preparation, model training, and deployment.

In January 2023, McKinsey & Company, a US-based management consulting firm, acquired Iguazio for $50 million. This acquisition was intended to accelerate and scale enterprise AI deployments by leveraging Iguazio's expertise in MLOps, a set of tools and practices for managing and scaling machine learning models in production. Iguazio is an Israel-based company providing machine learning model operationalization management.

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

North America was the largest region in the machine learning model operationalization management market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the machine learning model operationalization management market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

The countries covered in the machine learning model operationalization management market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The machine learning model operationalization management market includes revenues earned by entities by providing services such as model deployment, model monitoring, version control and rollback, integration with data pipelines, automated model retraining, and scalability and elasticity. The market value includes the value of related goods sold by the service provider or included within the service offering. The machine learning model operationalization management market also includes sales of central processing units (CPUs), graphics processing units (GPUs), and field-programmable gate arrays (FPGAs). Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Machine Learning Model Operationalization Management Global Market Report 2024 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on machine learning model operationalization management market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for machine learning model operationalization management? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward? The machine learning model operationalization management market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The impact of sanctions, supply chain disruptions, and altered demand for goods and services due to the Russian Ukraine war, impacting various macro-economic factors and parameters in the Eastern European region and its subsequent effect on global markets.

The impact of higher inflation in many countries and the resulting spike in interest rates.

The continued but declining impact of covid 19 on supply chains and consumption patterns.

Scope

Markets Covered:

Table of Contents

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. Global Machine Learning Model Operationalization Management Market Size and Growth

6. Machine Learning Model Operationalization Management Market Segmentation

7. Machine Learning Model Operationalization Management Market Regional And Country Analysis

8. Asia-Pacific Machine Learning Model Operationalization Management Market

9. China Machine Learning Model Operationalization Management Market

10. India Machine Learning Model Operationalization Management Market

11. Japan Machine Learning Model Operationalization Management Market

12. Australia Machine Learning Model Operationalization Management Market

13. Indonesia Machine Learning Model Operationalization Management Market

14. South Korea Machine Learning Model Operationalization Management Market

15. Western Europe Machine Learning Model Operationalization Management Market

16. UK Machine Learning Model Operationalization Management Market

17. Germany Machine Learning Model Operationalization Management Market

18. France Machine Learning Model Operationalization Management Market

19. Italy Machine Learning Model Operationalization Management Market

20. Spain Machine Learning Model Operationalization Management Market

21. Eastern Europe Machine Learning Model Operationalization Management Market

22. Russia Machine Learning Model Operationalization Management Market

23. North America Machine Learning Model Operationalization Management Market

24. USA Machine Learning Model Operationalization Management Market

25. Canada Machine Learning Model Operationalization Management Market

26. South America Machine Learning Model Operationalization Management Market

27. Brazil Machine Learning Model Operationalization Management Market

28. Middle East Machine Learning Model Operationalization Management Market

29. Africa Machine Learning Model Operationalization Management Market

30. Machine Learning Model Operationalization Management Market Competitive Landscape And Company Profiles

31. Machine Learning Model Operationalization Management Market Other Major And Innovative Companies

32. Global Machine Learning Model Operationalization Management Market Competitive Benchmarking

33. Global Machine Learning Model Operationalization Management Market Competitive Dashboard

34. Key Mergers And Acquisitions In The Machine Learning Model Operationalization Management Market

35. Machine Learning Model Operationalization Management Market Future Outlook and Potential Analysis

36. Appendix

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