USD 1.10 billion
Report ID:
SQMIG45D2064 |
Region:
Global |
Published Date: April, 2024
Pages:
197
|Tables:
59
|Figures:
75
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).
MLOps is the technology that empowers production-level machine learning. On the contrary, latest MLOps trends and predictions are emerging to meet the evolving challenges in scaling machine learning. The emerging advanced MLOps applications can solve a variety of human error and quality issues.
Hence, many organizations such as healthcare, IT, retail, and other sectors are adopting MLOps due to its benefits. This factor creates lucrative growth opportunities in the market. Surge in digital and internet penetration around the world is positively impacting the growth of the market.
In addition, increase in adoption of MLOps technology across enterprises to enhance operation & productivity, strengthens the growth of the market for the future. Furthermore, increasing investments in the healthcare sector is expected to provide the lucrative growth opportunities for the market during the forecast period.
Moreover, MLOps help to reduce costs over the entire machine learning lifecycle, creating numerous opportunities for market growth in the upcoming years. However, inaccessible data and data security, rigid business models and lack of engineering skills, hamper the MLOps market growth.
US MLOps Market is poised to grow at a sustainable CAGR for the next forecast year.
Global Market Size
USD 1.10 billion
Largest Segment
Model Infrastructure
Fastest Growth
Model Infrastructure
Growth Rate
41% CAGR
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The global MLOps market is segmented by infrastructure, data management, and region. Based on infrastructure, the market can be segmented into data infrastructure and model infrastructure. Based on data management the market is segmented into data pipeline management and data versioning. Based on region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
MLOps Market Analysis by Infrastructure
The infrastructure segment of MLOps involves setting up and managing the hardware and software components required for machine learning model development, deployment, and maintenance. It consists of two sub-segments:
Data infrastructure is the dominant sub-segment, and involves managing the data storage and processing components required for machine learning. It includes data storage technologies such as data lakes, databases, and data warehouses, along with data processing tools such as ETL (Extract, Transform, Load) pipelines and stream processing systems. Data infrastructure also includes managing the data versioning and tracking systems to keep track of changes made to the data for model training.
Model infrastructure sub-segment is the fastest growing sub-segment and involves managing the infrastructure for model development, deployment, and monitoring. It includes tools for version control, model training, and deployment such as deep learning frameworks, model serving platforms, and model monitoring tools. Model infrastructure also includes setting up the infrastructure for continuous integration and continuous deployment (CI/CD) pipelines for model updates and version control.
MLOps Market Analysis by Data Management
Data pipeline management involves building and maintaining automated workflows that move data from various sources to the machine learning models for training and inference. This will drive the demand in the coming years. For example, data pipeline management may involve building ETL (Extract, Transform, Load) workflows that pull data from a variety of sources such as databases, APIs, and file systems, transform it into a format suitable for machine learning models, and push it into the machine learning infrastructure.
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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.
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MLOps Market Drivers
Standardizing Ml Processes For Effective Teamwork
MLOps Market Restraints
Lack Of Expertise
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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.
MLOps Market Top Player’s Company Profiles
MLOps Market Recent Developments
SkyQuest’s ABIRAW (Advanced Business Intelligence, Research & Analysis Wing) is our Business Information Services team that Collects, Collates, Co-relates, and Analyses the Data collected by means of Primary Exploratory Research backed by robust Secondary Desk research.
MLOps, or machine learning operations, is the process of managing the entire lifecycle of machine learning models. This includes everything from development and training to deployment and monitoring. MLOps ensures that models are accurate, reliable, and scalable. It involves a combination of software engineering, data science, and operations management. MLOps is becoming increasingly important as machine learning is being used more widely in business applications. Effective MLOps can help organizations to improve their decision-making processes, increase efficiency, and reduce costs.
Report Metric | Details |
---|---|
Market size value in 2022 | USD 1.10 billion |
Market size value in 2031 | USD 24.23 billion |
Growth Rate | 41% |
Base year | 2023 |
Forecast period | 2024-2031 |
Forecast Unit (Value) | USD Billion |
Segments covered |
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Regions covered | North America (US, Canada), Europe (Germany, France, United Kingdom, Italy, Spain, Rest of Europe), Asia Pacific (China, India, Japan, Rest of Asia-Pacific), Latin America (Brazil, Rest of Latin America), Middle East & Africa (South Africa, GCC Countries, Rest of MEA) |
Companies covered |
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Customization scope | Free report customization with purchase. Customization includes:-
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Executive Summary
Market overview
Parent Market Analysis
Market overview
Market size
KEY MARKET INSIGHTS
COVID IMPACT
MARKET DYNAMICS & OUTLOOK
Market Size by Region
KEY COMPANY PROFILES
For the MLOps Market, our research methodology involved a mixture of primary and secondary data sources. Key steps involved in the research process are listed below:
1. Information Procurement: This stage involved the procurement of Market data or related information via primary and secondary sources. The various secondary sources used included various company websites, annual reports, trade databases, and paid databases such as Hoover's, Bloomberg Business, Factiva, and Avention. Our team did 45 primary interactions Globally which included several stakeholders such as manufacturers, customers, key opinion leaders, etc. Overall, information procurement was one of the most extensive stages in our research process.
2. Information Analysis: This step involved triangulation of data through bottom-up and top-down approaches to estimate and validate the total size and future estimate of the MLOps Market.
3. Report Formulation: The final step entailed the placement of data points in appropriate Market spaces in an attempt to deduce viable conclusions.
4. Validation & Publishing: Validation is the most important step in the process. Validation & re-validation via an intricately designed process helped us finalize data points to be used for final calculations. The final Market estimates and forecasts were then aligned and sent to our panel of industry experts for validation of data. Once the validation was done the report was sent to our Quality Assurance team to ensure adherence to style guides, consistency & design.
Customization Options
With the given market data, our dedicated team of analysts can offer you the following customization options are available for the MLOps Market:
Product Analysis: Product matrix, which offers a detailed comparison of the product portfolio of companies.
Regional Analysis: Further analysis of the MLOps Market for additional countries.
Competitive Analysis: Detailed analysis and profiling of additional Market players & comparative analysis of competitive products.
Go to Market Strategy: Find the high-growth channels to invest your marketing efforts and increase your customer base.
Innovation Mapping: Identify racial solutions and innovation, connected to deep ecosystems of innovators, start-ups, academics, and strategic partners.
Category Intelligence: Customized intelligence that is relevant to their supply Markets will enable them to make smarter sourcing decisions and improve their category management.
Public Company Transcript Analysis: To improve the investment performance by generating new alpha and making better-informed decisions.
Social Media Listening: To analyze the conversations and trends happening not just around your brand, but around your industry as a whole, and use those insights to make better Marketing decisions.
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Report ID: SQMIG45D2064
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