The machine learning model operationalization management (mlops) global market report 2024 from The Business Research Company provides comprehensive market statistics, including global market size, regional shares, competitor market share, detailed segments, trends, and opportunities. This report offers an in-depth analysis of current and future industry scenarios, delivering a complete perspective for thriving in the industrial automation software market.
Machine Learning Model Operationalization Management (MLOPS) Market, 2024 report by The Business Research Company offers comprehensive insights into the current state of the market and highlights future growth opportunities.
Market Size -
The
machine learning model operationalization management (mlops) market
size has grown exponentially in recent years. It will grow from $1.83
billion in 2023 to $2.65 billion in 2024 at a compound annual growth
rate (CAGR) of 44.9%. The growth in the historic period can be
attributed to proliferation of machine learning models, rising
complexity of ml models, growing data volumes, increasing demand for
automation, rise of cloud computing..
The machine learning model operationalization management (mlops) market size is expected to see exponential growth in the next few years. It will grow to $11.56 billion in 2028 at a compound annual growth rate (CAGR) of 44.6%. The growth in the forecast period can be attributed to advancements in model explainability, integration with ai governance, greater adoption of model versioning, focus on cost optimization, increased industry-specific solutions.. Major trends in the forecast period include advancements in technology, product innovations, cloud security initiatives, web applications development.
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Scope Of Machine Learning Model Operationalization Management (MLOPS) Market
The Business Research Company's reports encompass a wide range of information, including:
1. Market Size (Historic and Forecast): Analysis of the market's historical performance and projections for future growth.
2. Drivers: Examination of the key factors propelling market growth.
3. Trends: Identification of emerging trends and patterns shaping the market landscape.
4. Key Segments: Breakdown of the market into its primary segments and their respective performance.
5. Focus Regions and Geographies: Insight into the most critical regions and geographical areas influencing the market.
6. Macro Economic Factors: Assessment of broader economic elements impacting the market.
Machine Learning Model Operationalization Management (MLOPS) Market Overview
Market Drivers -
The
increasing adoption of AI technology is expected to propel the growth
of the machine learning model operationalization management (MLOPS)
market going forward. Artificial intelligence (AI) refers to the
development of computer systems or software that can perform tasks that
typically require human intelligence. Machine learning
operationalization management uses AI technology to ensure that machine
learning models are deployed, managed and monitored effectively in
production environments and enhance the end-to-end lifecycle of machine
learning (ML) models. For instance, in May 2022, according to a report
published by International Business Machines Corporation (IBM), a
US-based technology corporation, the adoption rate of AI globally
increased significantly and was at 35%, up four points from the previous
year. Further, in 2022, 13% more firms are projected to have used AI
than in 2021. 35% of organizations reported adopting AI in their
company, 42% are considering AI for adoption, and two-thirds of the
companies (66%) are either presently executing or intending to utilize
AI to meet their sustainability goals. Therefore, the increasing
adoption of AI technology is driving the growth of the machine learning
model operationalization management (MLOPS) market.
Market Trends -
The
increasing adoption of AI technology is expected to propel the growth
of the machine learning model operationalization management (MLOPS)
market going forward. Artificial intelligence (AI) refers to the
development of computer systems or software that can perform tasks that
typically require human intelligence. Machine learning
operationalization management uses AI technology to ensure that machine
learning models are deployed, managed, and monitored effectively in
production environments and to enhance the end-to-end lifecycle of
machine learning (ML) models. For instance, in May 2022, according to a
report published by International Business Machines Corporation (IBM), a
US-based technology corporation, the adoption rate of AI globally
increased significantly and was at 35%, up four points from the previous
year. Further, in 2022, 13% more firms are projected to have used AI
than in 2021. 35% of organizations reported adopting AI in their
company, 42% are considering AI for adoption, and two-thirds of the
companies (66%) are either presently executing or intending to utilize
AI to meet their sustainability goals. Therefore, the increasing
adoption of AI technology is driving the growth of the machine learning
model operationalization management (MLOPS) market.
The machine learning model operationalization management (mlops) market covered in this report is segmented –
1) By Component: Platform, Services
2) By Deployment: On-Premises, Cloud
3) By Organization Size: Large Enterprises, Small And Medium-Sized Enterprises
4)
By Vertical: Banking, Financial Services, And Insurance, Retail And
Ecommerce, Government And Defense, Health And Life Sciences,
Manufacturing, Telecom, IT And ITeS, Energy And Utilities,
Transportation And Logistics, Other Verticals
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Regional Insights -
North
America was the largest region in the machine learning model
operationalization management (MLOPS) market in 2023. The regions
covered in the machine learning model operationalization management
(mlops) market report are Asia-Pacific, Western Europe, Eastern Europe,
North America, South America, Middle East, Africa.
Key Companies -
Major
companies operating in the machine learning model operationalization
management (mlops) market report are Google LLC, Microsoft Corporation,
Amazon Web Services Inc., IBM Corporation, Oracle Corporation, SAP SE,
Hewlett Packard Enterprise Development LP, SAS Institute Inc.,
Informatica Corporation, Cloudera Inc., Databricks Inc , TIBCO Software
Inc., Alteryx Inc., DataRobot Inc, Dataiku Inc., Domino Data Lab Inc,
Neptune Labs, H2O.ai, RapidMiner, Tecton Inc, Data Science Dojo, ModelOp
Inc, Aible, Inc, Algorithmia, Inc, KNIME AG
Table of Contents
1. Executive Summary
2. Machine Learning Model Operationalization Management (MLOPS) Market Report Structure
3. Machine Learning Model Operationalization Management (MLOPS) Market Trends And Strategies
4. Machine Learning Model Operationalization Management (MLOPS) Market – Macro Economic Scenario
5. Machine Learning Model Operationalization Management (MLOPS) Market Size And Growth
…..
27. Machine Learning Model Operationalization Management (MLOPS) Market Competitor Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
30. Appendix
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