Global Machine Learning Operation Technology Market Research Report 2025

Publication ID:

PB503251642

Publication Date:

March 3, 2025

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

The global market for Machine Learning Operation Technology was valued at US$ million in the year 2024 and is projected to reach a revised size of US$ million by 2031, growing at a CAGR of %during the forecast period.
Machine Learning Operations is the process of taking an experimental Machine Learning model into a production system. The word is a compound of 鈥淢achine Learning鈥� and the continuous development practice of DevOps in the software field. Machine Learning models are tested and developed in isolated experimental systems. When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm to production systems. Similar to DevOps or DataOps approaches, MLOps seeks to increase automation and improve the quality of production models, while also focusing on business and regulatory requirements. While MLOps started as a set of best practices, it is slowly evolving into an independent approach to ML lifecycle management. MLOps applies to the entire lifecycle - from integrating with model generation (software development lifecycle, continuous integration/continuous delivery), orchestration, and deployment, to health, diagnostics, governance, and business metrics.
North American market for Machine Learning Operation Technology is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
Asia-Pacific market for Machine Learning Operation Technology is estimated to increase from $ million in 2024 to reach $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The global market for Machine Learning Operation Technology in BFSI is estimated to increase from $ million in 2024 to $ million by 2031, at a CAGR of % during the forecast period of 2025 through 2031.
The major global companies of Machine Learning Operation Technology include Microsoft, Amazon, Google, IBM, Dataiku, Lguazio, Databricks, DataRobot, Inc., Cloudera, Modzy, etc. In 2024, the world's top three vendors accounted for approximately % of the revenue.
This report aims to provide a comprehensive presentation of the global market for Machine Learning Operation Technology, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Machine Learning Operation Technology.
The Machine Learning Operation Technology market size, estimations, and forecasts are provided in terms of and revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. This report segments the global Machine Learning Operation Technology market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Machine Learning Operation Technology companies, new entrants, and industry chain related companies in this market with information on the revenues for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
Microsoft
Amazon
Google
IBM
Dataiku
Lguazio
Databricks
DataRobot, Inc.
Cloudera
Modzy
Algorithmia
HPE
Valohai
Allegro AI
Comet
FloydHub
Paperpace
Cnvrg.io
Segment by Type
On-premise
Cloud
Segment by Application
BFSI
Healthcare
Retail
Manufacturing
Public Sector
Others
By Region
North America
United States
Canada
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Europe
Germany
France
U.K.
Italy
Russia
Nordic Countries
Rest of Europe
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Machine Learning Operation Technology company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Machine Learning Operation Technology Market Size Growth Rate by Type: 2020 VS 2024 VS 2031
1.2.2 On-premise
1.2.3 Cloud
1.3 Market by Application
1.3.1 Global Machine Learning Operation Technology Market Growth by Application: 2020 VS 2024 VS 2031
1.3.2 BFSI
1.3.3 Healthcare
1.3.4 Retail
1.3.5 Manufacturing
1.3.6 Public Sector
1.3.7 Others
1.4 Assumptions and Limitations
1.5 Study Objectives
1.6 Years Considered
2 Global Growth Trends
2.1 Global Machine Learning Operation Technology Market Perspective (2020-2031)
2.2 Global Machine Learning Operation Technology Growth Trends by Region
2.2.1 Global Machine Learning Operation Technology Market Size by Region: 2020 VS 2024 VS 2031
2.2.2 Machine Learning Operation Technology Historic Market Size by Region (2020-2025)
2.2.3 Machine Learning Operation Technology Forecasted Market Size by Region (2026-2031)
2.3 Machine Learning Operation Technology Market Dynamics
2.3.1 Machine Learning Operation Technology Industry Trends
2.3.2 Machine Learning Operation Technology Market Drivers
2.3.3 Machine Learning Operation Technology Market Challenges
2.3.4 Machine Learning Operation Technology Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Machine Learning Operation Technology Players by Revenue
3.1.1 Global Top Machine Learning Operation Technology Players by Revenue (2020-2025)
3.1.2 Global Machine Learning Operation Technology Revenue Market Share by Players (2020-2025)
3.2 Global Machine Learning Operation Technology Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Global Key Players Ranking by Machine Learning Operation Technology Revenue
3.4 Global Machine Learning Operation Technology Market Concentration Ratio
3.4.1 Global Machine Learning Operation Technology Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Machine Learning Operation Technology Revenue in 2024
3.5 Global Key Players of Machine Learning Operation Technology Head office and Area Served
3.6 Global Key Players of Machine Learning Operation Technology, Product and Application
3.7 Global Key Players of Machine Learning Operation Technology, Date of Enter into This Industry
3.8 Mergers & Acquisitions, Expansion Plans
4 Machine Learning Operation Technology Breakdown Data by Type
4.1 Global Machine Learning Operation Technology Historic Market Size by Type (2020-2025)
4.2 Global Machine Learning Operation Technology Forecasted Market Size by Type (2026-2031)
5 Machine Learning Operation Technology Breakdown Data by Application
5.1 Global Machine Learning Operation Technology Historic Market Size by Application (2020-2025)
5.2 Global Machine Learning Operation Technology Forecasted Market Size by Application (2026-2031)
6 North America
6.1 North America Machine Learning Operation Technology Market Size (2020-2031)
6.2 North America Machine Learning Operation Technology Market Growth Rate by Country: 2020 VS 2024 VS 2031
6.3 North America Machine Learning Operation Technology Market Size by Country (2020-2025)
6.4 North America Machine Learning Operation Technology Market Size by Country (2026-2031)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Machine Learning Operation Technology Market Size (2020-2031)
7.2 Europe Machine Learning Operation Technology Market Growth Rate by Country: 2020 VS 2024 VS 2031
7.3 Europe Machine Learning Operation Technology Market Size by Country (2020-2025)
7.4 Europe Machine Learning Operation Technology Market Size by Country (2026-2031)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Machine Learning Operation Technology Market Size (2020-2031)
8.2 Asia-Pacific Machine Learning Operation Technology Market Growth Rate by Region: 2020 VS 2024 VS 2031
8.3 Asia-Pacific Machine Learning Operation Technology Market Size by Region (2020-2025)
8.4 Asia-Pacific Machine Learning Operation Technology Market Size by Region (2026-2031)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Machine Learning Operation Technology Market Size (2020-2031)
9.2 Latin America Machine Learning Operation Technology Market Growth Rate by Country: 2020 VS 2024 VS 2031
9.3 Latin America Machine Learning Operation Technology Market Size by Country (2020-2025)
9.4 Latin America Machine Learning Operation Technology Market Size by Country (2026-2031)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Machine Learning Operation Technology Market Size (2020-2031)
10.2 Middle East & Africa Machine Learning Operation Technology Market Growth Rate by Country: 2020 VS 2024 VS 2031
10.3 Middle East & Africa Machine Learning Operation Technology Market Size by Country (2020-2025)
10.4 Middle East & Africa Machine Learning Operation Technology Market Size by Country (2026-2031)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 Microsoft
11.1.1 Microsoft Company Details
11.1.2 Microsoft Business Overview
11.1.3 Microsoft Machine Learning Operation Technology Introduction
11.1.4 Microsoft Revenue in Machine Learning Operation Technology Business (2020-2025)
11.1.5 Microsoft Recent Development
11.2 Amazon
11.2.1 Amazon Company Details
11.2.2 Amazon Business Overview
11.2.3 Amazon Machine Learning Operation Technology Introduction
11.2.4 Amazon Revenue in Machine Learning Operation Technology Business (2020-2025)
11.2.5 Amazon Recent Development
11.3 Google
11.3.1 Google Company Details
11.3.2 Google Business Overview
11.3.3 Google Machine Learning Operation Technology Introduction
11.3.4 Google Revenue in Machine Learning Operation Technology Business (2020-2025)
11.3.5 Google Recent Development
11.4 IBM
11.4.1 IBM Company Details
11.4.2 IBM Business Overview
11.4.3 IBM Machine Learning Operation Technology Introduction
11.4.4 IBM Revenue in Machine Learning Operation Technology Business (2020-2025)
11.4.5 IBM Recent Development
11.5 Dataiku
11.5.1 Dataiku Company Details
11.5.2 Dataiku Business Overview
11.5.3 Dataiku Machine Learning Operation Technology Introduction
11.5.4 Dataiku Revenue in Machine Learning Operation Technology Business (2020-2025)
11.5.5 Dataiku Recent Development
11.6 Lguazio
11.6.1 Lguazio Company Details
11.6.2 Lguazio Business Overview
11.6.3 Lguazio Machine Learning Operation Technology Introduction
11.6.4 Lguazio Revenue in Machine Learning Operation Technology Business (2020-2025)
11.6.5 Lguazio Recent Development
11.7 Databricks
11.7.1 Databricks Company Details
11.7.2 Databricks Business Overview
11.7.3 Databricks Machine Learning Operation Technology Introduction
11.7.4 Databricks Revenue in Machine Learning Operation Technology Business (2020-2025)
11.7.5 Databricks Recent Development
11.8 DataRobot, Inc.
11.8.1 DataRobot, Inc. Company Details
11.8.2 DataRobot, Inc. Business Overview
11.8.3 DataRobot, Inc. Machine Learning Operation Technology Introduction
11.8.4 DataRobot, Inc. Revenue in Machine Learning Operation Technology Business (2020-2025)
11.8.5 DataRobot, Inc. Recent Development
11.9 Cloudera
11.9.1 Cloudera Company Details
11.9.2 Cloudera Business Overview
11.9.3 Cloudera Machine Learning Operation Technology Introduction
11.9.4 Cloudera Revenue in Machine Learning Operation Technology Business (2020-2025)
11.9.5 Cloudera Recent Development
11.10 Modzy
11.10.1 Modzy Company Details
11.10.2 Modzy Business Overview
11.10.3 Modzy Machine Learning Operation Technology Introduction
11.10.4 Modzy Revenue in Machine Learning Operation Technology Business (2020-2025)
11.10.5 Modzy Recent Development
11.11 Algorithmia
11.11.1 Algorithmia Company Details
11.11.2 Algorithmia Business Overview
11.11.3 Algorithmia Machine Learning Operation Technology Introduction
11.11.4 Algorithmia Revenue in Machine Learning Operation Technology Business (2020-2025)
11.11.5 Algorithmia Recent Development
11.12 HPE
11.12.1 HPE Company Details
11.12.2 HPE Business Overview
11.12.3 HPE Machine Learning Operation Technology Introduction
11.12.4 HPE Revenue in Machine Learning Operation Technology Business (2020-2025)
11.12.5 HPE Recent Development
11.13 Valohai
11.13.1 Valohai Company Details
11.13.2 Valohai Business Overview
11.13.3 Valohai Machine Learning Operation Technology Introduction
11.13.4 Valohai Revenue in Machine Learning Operation Technology Business (2020-2025)
11.13.5 Valohai Recent Development
11.14 Allegro AI
11.14.1 Allegro AI Company Details
11.14.2 Allegro AI Business Overview
11.14.3 Allegro AI Machine Learning Operation Technology Introduction
11.14.4 Allegro AI Revenue in Machine Learning Operation Technology Business (2020-2025)
11.14.5 Allegro AI Recent Development
11.15 Comet
11.15.1 Comet Company Details
11.15.2 Comet Business Overview
11.15.3 Comet Machine Learning Operation Technology Introduction
11.15.4 Comet Revenue in Machine Learning Operation Technology Business (2020-2025)
11.15.5 Comet Recent Development
11.16 FloydHub
11.16.1 FloydHub Company Details
11.16.2 FloydHub Business Overview
11.16.3 FloydHub Machine Learning Operation Technology Introduction
11.16.4 FloydHub Revenue in Machine Learning Operation Technology Business (2020-2025)
11.16.5 FloydHub Recent Development
11.17 Paperpace
11.17.1 Paperpace Company Details
11.17.2 Paperpace Business Overview
11.17.3 Paperpace Machine Learning Operation Technology Introduction
11.17.4 Paperpace Revenue in Machine Learning Operation Technology Business (2020-2025)
11.17.5 Paperpace Recent Development
11.18 Cnvrg.io
11.18.1 Cnvrg.io Company Details
11.18.2 Cnvrg.io Business Overview
11.18.3 Cnvrg.io Machine Learning Operation Technology Introduction
11.18.4 Cnvrg.io Revenue in Machine Learning Operation Technology Business (2020-2025)
11.18.5 Cnvrg.io Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.1.1 Research Programs/Design
13.1.1.2 Market Size Estimation
13.1.1.3 Market Breakdown and Data Triangulation
13.1.2 Data Source
13.1.2.1 Secondary Sources
13.1.2.2 Primary Sources
13.2 Author Details
13.3 Disclaimer

Companies Mentioned:

Microsoft
Amazon
Google
IBM
Dataiku
Lguazio
Databricks
DataRobot, Inc.
Cloudera
Modzy
Algorithmia
HPE
Valohai
Allegro AI
Comet
FloydHub
Paperpace
Cnvrg.io

License Types:

Single User License (PDF)

This license allows for use of a publication by one person.
This person may print out a single copy of the publication.
This person can include information given in the publication in presentations and internal reports by providing full copyright credit to the publisher.
This person cannot share the publication (or any information contained therein) with any other person or persons.
Unless a Enterprise License is purchased, a Single User License must be purchased for every person that wishes to use the publication within the same organization.
Customers who infringe these license terms are liable for a Global license fee.

听

Site License (PDF)*

This license allows for use of a publication by all users within one corporate location, e.g. a regional office.
These users may print out a single copy of the publication.
These users can include information given in the publication in presentations and internal reports by providing full copyright credit to the publisher.
These users cannot share the publication (or any information contained therein) with any other person or persons outside the corporate location for which the publication is purchased.
Unless a Enterprise License is purchased, a Site User License must be purchased for every corporate location by an organization that wishes to use the publication within the same organization.
Customers who infringe these license terms are liable for a Global license fee.

听

Global License (PDF)*

This license allows for use of a publication by unlimited users within the purchasing organization e.g. all employees of a single company.
Each of these people may use the publication on any computer, and may print out the report, but may not share the publication (or any information contained therein) with any other person or persons outside of the organization.
These employees of purchasing organization can include information given in the publication in presentations and internal reports by providing full copyright credit to the publisher.

*If Applicable.

91制片厂