The Latin America, Middle East and Africa Machine Learning Model Operationalization Management (MLOps) Market should witness market growth of 47.2% CAGR during the forecast period (2022-2028).
MLOps projects frequently aim to hasten the model deployment process because that is when models begin to produce commercial value. According to MLOps, putting in more work upfront would boost the long-term value of implemented ML solutions by decreasing maintenance costs and streamlining the deployment of new models.
The main goal of a machine learning project is to build a statistical model using collected data and machine learning methods. Data, ML models, and code are thus the three primary artefacts of every ML-based product.
More businesses are testing machine learning (ML). Both a model and its implementation in the real world must be built. Teams must integrate the trained ML model into the core codebase to fully utilize the built ML model by making it accessible to our core software system. Teams must therefore put the ML model into production.
The oil-rich Gulf States are aggressively working to diversify their economies throughout the Middle East and Africa utilizing artificial intelligence and machine learning. The majority of Gulf nations, which are constantly seeking to develop new technologies, have acknowledged the significance of modern technology. The Arab region is led by the United Arab Emirates in terms of technical innovation and acceptance. Additionally, the region's focus on smart cities and driverless vehicles is driving demand for AI expertise.
The Brazil market dominated the LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $182 million by 2028. The Argentina market is experiencing a CAGR of 48% during (2022-2028). Additionally, The UAE market would display a CAGR of 46.8% during (2022-2028).
Based on Component, the market is segmented into Platform and Services. Based on Vertical, the market is segmented into BFSI, IT & ITeS, Manufacturing, Retail & Ecommerce, Government & Defense, Healthcare & Life Sciences, Telecom, Energy & Utilities, Travel & Tourism, and Others. Based on Organization size, the market is segmented into Large Enterprises and SMEs. Based on Deployment Mode, the market is segmented into Cloud and On-premise. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Amazon Web Services, Inc. (Amazon.com, Inc.), Google LLC, IBM Corporation, Hewlett-Packard enterprise Company, Alteryx, Inc., Cloudera, Inc., DataRobot, Inc., Domino Data Lab, Inc., and H2O.ai, Inc.
MLOps projects frequently aim to hasten the model deployment process because that is when models begin to produce commercial value. According to MLOps, putting in more work upfront would boost the long-term value of implemented ML solutions by decreasing maintenance costs and streamlining the deployment of new models.
The main goal of a machine learning project is to build a statistical model using collected data and machine learning methods. Data, ML models, and code are thus the three primary artefacts of every ML-based product.
More businesses are testing machine learning (ML). Both a model and its implementation in the real world must be built. Teams must integrate the trained ML model into the core codebase to fully utilize the built ML model by making it accessible to our core software system. Teams must therefore put the ML model into production.
The oil-rich Gulf States are aggressively working to diversify their economies throughout the Middle East and Africa utilizing artificial intelligence and machine learning. The majority of Gulf nations, which are constantly seeking to develop new technologies, have acknowledged the significance of modern technology. The Arab region is led by the United Arab Emirates in terms of technical innovation and acceptance. Additionally, the region's focus on smart cities and driverless vehicles is driving demand for AI expertise.
The Brazil market dominated the LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Country in 2021, and would continue to be a dominant market till 2028; thereby, achieving a market value of $182 million by 2028. The Argentina market is experiencing a CAGR of 48% during (2022-2028). Additionally, The UAE market would display a CAGR of 46.8% during (2022-2028).
Based on Component, the market is segmented into Platform and Services. Based on Vertical, the market is segmented into BFSI, IT & ITeS, Manufacturing, Retail & Ecommerce, Government & Defense, Healthcare & Life Sciences, Telecom, Energy & Utilities, Travel & Tourism, and Others. Based on Organization size, the market is segmented into Large Enterprises and SMEs. Based on Deployment Mode, the market is segmented into Cloud and On-premise. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Microsoft Corporation, Amazon Web Services, Inc. (Amazon.com, Inc.), Google LLC, IBM Corporation, Hewlett-Packard enterprise Company, Alteryx, Inc., Cloudera, Inc., DataRobot, Inc., Domino Data Lab, Inc., and H2O.ai, Inc.
Scope of the Study
By Component
- Platform
- Services
By Vertical
- BFSI
- IT & ITeS
- Manufacturing
- Retail & Ecommerce
- Government & Defense
- Healthcare & Life Sciences
- Telecom
- Energy & Utilities
- Travel & Tourism
- Others
By Organization size
- Large Enterprises
- SMEs
By Deployment Mode
- Cloud
- On-premise
By Country
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Key Market Players
List of Companies Profiled in the Report:
- Microsoft Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Google LLC
- IBM Corporation
- Hewlett-Packard enterprise Company
- Alteryx, Inc.
- Cloudera, Inc.
- DataRobot, Inc.
- Domino Data Lab, Inc.
- H2O.ai, Inc.
Unique Offerings
- Exhaustive coverage
- The highest number of market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 LAMEA Machine Learning Model Operationalization Management (MLOps) Market, by Component
1.4.2 LAMEA Machine Learning Model Operationalization Management (MLOps) Market, by Vertical
1.4.3 LAMEA Machine Learning Model Operationalization Management (MLOps) Market, by Organization size
1.4.4 LAMEA Machine Learning Model Operationalization Management (MLOps) Market, by Deployment Mode
1.4.5 LAMEA Machine Learning Model Operationalization Management (MLOps) Market, by Country
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.3.2 Key Strategic Move: (Product Launches and Product Expansions : 2018, Nov - 2022, Dec) Leading Players
Chapter 4. LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Component
4.1 LAMEA Platform Market by Country
4.2 LAMEA Services Market by Country
Chapter 5. LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Vertical
5.1 LAMEA BFSI Market by Country
5.2 LAMEA IT & ITeS Market by Country
5.3 LAMEA Manufacturing Market by Country
5.4 LAMEA Retail & Ecommerce Market by Country
5.5 LAMEA Government & Defense Market by Country
5.6 LAMEA Healthcare & Life Sciences Market by Country
5.7 LAMEA Telecom Market by Country
5.8 LAMEA Energy & Utilities Market by Country
5.9 LAMEA Travel & Tourism Market by Country
5.1 LAMEA Other Vertical Market by Country
Chapter 6. LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Organization size
6.1 LAMEA Large Enterprises Market by Country
6.2 LAMEA SMEs Market by Country
Chapter 7. LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
7.1 LAMEA Cloud Market by Country
7.2 LAMEA On-premise Market by Country
Chapter 8. LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Country
8.1 Brazil Machine Learning Model Operationalization Management (MLOps) Market
8.1.1 Brazil Machine Learning Model Operationalization Management (MLOps) Market by Component
8.1.2 Brazil Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.1.3 Brazil Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.1.4 Brazil Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
8.2 Argentina Machine Learning Model Operationalization Management (MLOps) Market
8.2.1 Argentina Machine Learning Model Operationalization Management (MLOps) Market by Component
8.2.2 Argentina Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.2.3 Argentina Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.2.4 Argentina Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
8.3 UAE Machine Learning Model Operationalization Management (MLOps) Market
8.3.1 UAE Machine Learning Model Operationalization Management (MLOps) Market by Component
8.3.2 UAE Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.3.3 UAE Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.3.4 UAE Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
8.4 Saudi Arabia Machine Learning Model Operationalization Management (MLOps) Market
8.4.1 Saudi Arabia Machine Learning Model Operationalization Management (MLOps) Market by Component
8.4.2 Saudi Arabia Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.4.3 Saudi Arabia Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.4.4 Saudi Arabia Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
8.5 South Africa Machine Learning Model Operationalization Management (MLOps) Market
8.5.1 South Africa Machine Learning Model Operationalization Management (MLOps) Market by Component
8.5.2 South Africa Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.5.3 South Africa Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.5.4 South Africa Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
8.6 Nigeria Machine Learning Model Operationalization Management (MLOps) Market
8.6.1 Nigeria Machine Learning Model Operationalization Management (MLOps) Market by Component
8.6.2 Nigeria Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.6.3 Nigeria Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.6.4 Nigeria Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
8.7 Rest of LAMEA Machine Learning Model Operationalization Management (MLOps) Market
8.7.1 Rest of LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Component
8.7.2 Rest of LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Vertical
8.7.3 Rest of LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Organization size
8.7.4 Rest of LAMEA Machine Learning Model Operationalization Management (MLOps) Market by Deployment Mode
Chapter 9. Company Profiles
9.1 Microsoft Corporation
9.1.1 Company Overview
9.1.2 Financial Analysis
9.1.4 Research & Development Expenses
9.1.5 Recent strategies and developments:
9.1.5.1 Partnerships, Collaborations, and Agreements:
9.1.5.2 Product Launches and Product Expansions:
9.1.6 SWOT Analysis
9.2 Amazon Web Services, Inc. (Amazon.com, Inc.)
9.2.1 Company Overview
9.2.2 Financial Analysis
9.2.3 Segmental Analysis
9.2.4 Recent strategies and developments:
9.2.4.1 Partnerships, Collaborations, and Agreements:
9.2.4.2 Product Launches and Product Expansions:
9.2.5 SWOT Analysis
9.3 Google LLC
9.3.1 Company Overview
9.3.2 Financial Analysis
9.3.3 Segmental and Regional Analysis
9.3.4 Research & Development Expense
9.3.5 Recent strategies and developments:
9.3.5.1 Product Launches and Product Expansions:
9.3.6 SWOT Analysis
9.4 IBM Corporation
9.4.1 Company Overview
9.4.2 Financial Analysis
9.4.3 Regional & Segmental Analysis
9.4.4 Research & Development Expenses
9.4.5 Recent strategies and developments:
9.4.5.1 Acquisition and Mergers:
9.4.1 SWOT Analysis
9.5 Hewlett Packard Enterprise Company
9.5.1 Company Overview
9.5.2 Financial Analysis
9.5.3 Segmental and Regional Analysis
9.5.4 Research & Development Expense
9.5.5 Recent strategies and developments:
9.5.5.1 Product Launches and Product Expansions:
9.5.5.2 Acquisition and Mergers:
9.6 Alteryx, Inc.
9.6.1 Company Overview
9.6.2 Financial Analysis
9.6.3 Regional Analysis
9.6.4 Research & Development Expense
9.6.5 Recent strategies and developments:
9.6.5.1 Product Launches and Product Expansions:
9.7 Cloudera, Inc.
9.7.1 Company Overview
9.7.2 Financial Analysis
9.7.3 Segmental Analysis
9.7.4 Research & Development Expense
9.8 DataRobot, Inc.
9.8.1 Company Overview
9.8.2 Recent strategies and developments:
9.8.2.1 Acquisition and Mergers:
9.9 Domino Data Lab, Inc.
9.9.1 Company Overview
9.9.2 Recent strategies and developments:
9.9.2.1 Partnerships, Collaborations, and Agreements:
9.9.2.2 Product Launches and Product Expansions:
9.10. H2O.ai, Inc.
9.10.1 Company Overview
9.10.2 Recent strategies and developments:
9.10.2.1 Partnerships, Collaborations, and Agreements:
9.10.2.2 Product Launches and Product Expansions:
Companies Mentioned
- Microsoft Corporation
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- Google LLC
- IBM Corporation
- Hewlett-Packard enterprise Company
- Alteryx, Inc.
- Cloudera, Inc.
- DataRobot, Inc.
- Domino Data Lab, Inc.
- H2O.ai, Inc.
Methodology
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