MLOps Market

MLOps Market by Component (Platform and Services), Deployment Mode (Cloud and On-premises), Organization Size (Large Enterprises and SMEs), Vertical (BFSI, Healthcare and Life Sciences, Retail and eCommerce, Telecom) and Region - Global Forecast to 2027

Report Code: TC 8518 Dec, 2022, by marketsandmarkets.com

[219 Pages Report] The MLOps market size is projected to grow from USD 1.1 billion in 2022 to USD 5.9 billion by 2027, at a CAGR of 41.0% during the forecast period. Standardizing ML processes for effective teamwork has fueled the demand of MLOps. Moreover, monitorability and scalability is expected to drive the market growth for MLOps Market. Particularly MLOps reduces friction between DevOps and IT, promotes tighter cooperation between data teams, makes ML pipelines repeatable, and accelerates up release velocity.

MLOps Market

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MLOps Market Dynamics:

Driver: Standardizing ML processes for effective teamwork

Manual data reprocessing and collecting are ineffective and might produce unsatisfactory results. MLOps helps for automating the whole ML model workflow. This includes data gathering, model construction, testing, retraining, and deployment. MLOps help companies save time and reduce error rates. Collaboration is seen between IT and business personnel, as well as data scientists and engineers, for the company-wide adoption of ML models. Businesses can standardize ML operations and establish a standardized language for all participants due to MLOps principles. This reduces compatibility problems and quickens the construction and deployment of modelling processes.

Restraint: Lack of expertise

In order to gather and integrate the vast volumes of data from multiple internal and external data sources, as well as to merge the data silos, organisations should now use MLOps in data management. However, they are unable to embrace MLOps models due to knowledge gaps and a lack of worker capabilities. Organizations frequently operate in silos; thus, the necessity for MLOps models is becoming increasingly crucial in order to acquire a broader picture of many applications and verticals. Surveys have frequently demonstrated the inadequate knowledge and abilities of the employees in enterprises, according to numerous reports and research. Organizations should prioritise and make significant investments in training and certifications to address this issue, ensuring that the workforce has the necessary understanding of MLOps models and strategies and can put those tactics into practise for effective data management.

Opportunity: Expanded Use of Machine Leading in the Financial Sector

The customer data that financial companies hold is enormous. To generate a 360-degree image of the consumer, they might gather data on purchases, expenditure patterns, platform utilization, and geo-locational choices in along with traditional banking details, including bank account balances. This permits the bank to provide services and products that are specifically customized to the needs and preferences of the consumer. Data analysis and the creation of individualized service and promotional offerings may be done extremely effectively with the aid of machine learning algorithms.

Challenge: Raw Data Manipulation

Raw data is utilized to generate predictions and extract final outcomes when a model is put into production. Therefore, it becomes challenging to determine the model's correctness and continually assess it. Manually labelling the new data delays the process and is ineffective for ongoing retraining tasks. It also depends on the issue and the task's objectives whether to use the trained model to label the fresh data or to utilize unsupervised learning rather than supervised learning. There are some data kinds where labelling is not necessary. Due to this, businesses find it challenging to integrate MLOps into their routine operations to handle their raw data, which might result in data manipulation.

By component, platform segment holds largest market size during forecast period

Technological developments have created a new edge of digitalization where advanced MLOps solutions are adopted at a large scale in various enterprises across the globe. MLOps solutions help in increasing the overall productivity of the remote workforce and reduce the costs associated with traveling and engagement. Thus, the solutions play a crucial role in reducing the overall OPEX and Capital Expenditure (CAPEX). Effective enterprise collaboration offers a seamless video experience for various application areas, such as marketing, client engagement, knowledge sharing, team collaboration, and employee training. The advanced MLOps solutions also comply with regulations, such as HIPPA and GDPR, making it easier for highly regulated industries to adopt these solutions.

North America is expected to hold largest market share during forecast period

North America 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.

MLOps Market Size, and Share

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Market Players:

The major players in the MLOps market IBM (US), Microsoft (US), Google (US), AWS (US), HPE (US), GAVS Technologies (US), DataRobot (US), Cloudera (US), Alteryx (US), Domino Data Lab (US), Valohai (US), H2O.ai (US), MLflow (Netherlands), Neptune.ai (Europe), Comet (US), SparkCognition (US), Hopsworks (Europe), Datatron (US), Weights & Biases (US), Katonic.ai (Australia), Modzy (US), Iguazio (Israel), Teliolabs (US), ClearML (Israel), Akira.AI (India), and Blaize (US). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches and product enhancements, and acquisitions, to expand their footprint in the MLOps market.

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Scope of the Report

Report Metrics

Details

Market size available for years 2018–2027
Base year considered 2021
Forecast period 2022–2027
Forecast units Value (USD) Million/Billion
Segments covered Component, Deployment mode, Organization size, Vertical
Region covered North America, Europe, Asia Pacific, Middle East and Africa, and Latin America
Companies covered Major Vendors - - IBM (US), Microsoft (US), Google (US), AWS (US), HPE (US), GAVS Technologies (US), DataRobot (US), Cloudera (US), and Alteryx (US)
Startup/SME Vendors - Domino Data Lab (US), Valohai (US), H2O.ai (US), MLflow (Netherlands), Neptune.ai (Europe), Comet (US), SparkCognition (US), Hopsworks (Europe), Datatron (US), Weights & Biases (US), Katonic.ai (Australia), Modzy (US), Iguazio (Israel), Teliolabs (US), ClearML (Israel), Akira.AI (India), and Blaize (US).

This research report categorizes the MLOps market to forecast revenues and analyze trends in each of the following submarkets:

Based on Component:
  • Platform
  • Services
Based on Deployment Mode:
  • On-Premises
  • Cloud
Based on Organization Size:
  • Large Enterprises
  • SMEs
Based on Vertical:
  • Banking, Financial Services, and Insurance
  • Retail and eCommerce
  • Government and Defense
  • Healthcare and Life Sciences
  • Manufacturing
  • Telecom
  • IT and ITeS
  • Energy and Utilities
  • Transportation and Logistics
  • Other Verticals
By Region:
  • North America
    • United States (US)
    • Canada
  • Europe
    • United Kingdom (UK)
    • Germany
    • France
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • Rest of Asia Pacific
  • Middle East and Africa
    • KSA
    • UAE
    • South Africa
    • Rest of Middle East and Africa
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America

Recent Developments

  • In September 2022, Cloudera announced its strategic partnership with Meralco to create a unique solution, a flagship analytics platform that analyzes Meralco’s data and runs several ML models.
  • In June 2022, DataRobot announced the release of advanced AI Cloud with new and improved business impact.
  • In May 2022, GAVS Technologies announced its partnership with NTT Ltd. This partnership incorporated integration of ZIF AIOps platform to NTT Ltd.'s Infrastructure Managed Services (IMS).
  • In February 2022, HPE and Ayar Labs announced a multi-year strategic collaboration to usher in a new age of data centre innovation through the development of silicon photonics solutions based on optical I/O technology.
  • In September 2021, DataRobot collaborated with Foxtons, the top estate agency in London to expedite its data analytics and modelling capabilities in order to better serve consumers and make more strategic data-driven business choices.
  • In January 2021, Alteryx partners with Snowflake, to serve the market growing demand. The partnership integrates Alteryx data science and automation capabilities with Snowflake’s platform to serve collective customers base with automated data pipelining, faster data processing, and boosts analytics at scale.

Frequently Asked Questions (FAQ):

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TABLE OF CONTENTS
 
1 INTRODUCTION (Page No. - 22)
    1.1 STUDY OBJECTIVES 
    1.2 MARKET DEFINITION 
           1.2.1 INCLUSIONS AND EXCLUSIONS
    1.3 MARKET SCOPE 
           1.3.1 MARKET SEGMENTATION
           1.3.2 REGIONS COVERED
           1.3.3 YEARS CONSIDERED
    1.4 CURRENCY CONSIDERED 
           TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2019–2021
    1.5 STAKEHOLDERS 
 
2 RESEARCH METHODOLOGY (Page No. - 26)
    2.1 RESEARCH DATA 
           FIGURE 1 MLOPS: RESEARCH DESIGN
           2.1.1 SECONDARY DATA
           2.1.2 PRIMARY DATA
                    TABLE 2 PRIMARY INTERVIEWS
                    2.1.2.1 Breakup of primary profiles
                    2.1.2.2 Key industry insights
    2.2 MARKET BREAKUP AND DATA TRIANGULATION 
           FIGURE 2 DATA TRIANGULATION
    2.3 MARKET SIZE ESTIMATION 
           FIGURE 3 MLOPS: TOP-DOWN AND BOTTOM-UP APPROACHES
           2.3.1 TOP-DOWN APPROACH
           2.3.2 BOTTOM-UP APPROACH
                    FIGURE 4 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): REVENUE FROM MLOPS SOLUTIONS/SERVICES
                    FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL MLOPS PLATFORMS/SERVICES
                    FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3,  BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE  FROM ALL MLOPS PLATFORMS/SERVICES
                    FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): SHARE OF MLOPS THROUGH OVERALL MLOPS SPENDING
    2.4 MARKET FORECAST 
           TABLE 3 FACTOR ANALYSIS
    2.5 COMPANY EVALUATION MATRIX METHODOLOGY 
           FIGURE 8 COMPANY EVALUATION MATRIX: CRITERIA WEIGHTAGE
    2.6 STARTUP/SME EVALUATION MATRIX METHODOLOGY 
           FIGURE 9 STARTUP/SME EVALUATION MATRIX: CRITERIA WEIGHTAGE
    2.7 ASSUMPTIONS 
    2.8 LIMITATIONS 
 
3 EXECUTIVE SUMMARY (Page No. - 40)
                    TABLE 4 GLOBAL MLOPS MARKET SIZE AND GROWTH RATE, 2018–2021 (USD MILLION, Y-O-Y%)
                               TABLE 5 GLOBAL MARKET SIZE AND GROWTH RATE, 2022–2027 (USD MILLION, Y-O-Y%)
                               FIGURE 10 PLATFORMS SEGMENT TO LEAD MARKET IN 2022
                               FIGURE 11 CONSULTING SERVICES SEGMENT TO HOLD LARGEST MARKET SHARE IN 2022
                               FIGURE 12 CLOUD SEGMENT TO ACCOUNT FOR LARGER MARKET SIZE IN 2022
                               FIGURE 13 LARGE ENTERPRISES SEGMENT TO DOMINATE MARKET IN 2022
                               FIGURE 14 BANKING, FINANCIAL SERVICES& INSURANCE VERTICAL TO LEAD MARKET  IN 2022
                               FIGURE 15 NORTH AMERICA TO HOLD LARGEST MARKET SHARE IN 2022
 
4 PREMIUM INSIGHTS (Page No. - 44)
    4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN  MLOPS MARKET 
           FIGURE 16 HIGH DEMAND FOR DATA-DRIVEN INSIGHTS PLATFORM TO DRIVE MARKET DURING FORECAST PERIOD
    4.2 MARKET, BY VERTICAL 
           FIGURE 17 BANKING, FINANCIAL SERVICES & INSURANCE VERTICAL TO LEAD MARKET DURING FORECAST PERIOD
    4.3 MARKET, BY REGION 
           FIGURE 18 NORTH AMERICA TO ACCOUNT FOR LARGEST MARKET SHARE BY 2026
    4.4 NORTH AMERICA: MARKET,  BY COMPONENT AND COUNTRY 
           FIGURE 19 PLATFORMS SEGMENT AND US TO DOMINATE NORTH AMERICAN MARKET  IN 2022
 
5 MARKET OVERVIEW AND INDUSTRY TRENDS (Page No. - 46)
    5.1 INTRODUCTION 
    5.2 MARKET DYNAMICS 
           FIGURE 20 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: MLOPS MARKET
           5.2.1 DRIVERS
                    5.2.1.1 Standardization of ML processes for effective teamwork
                    5.2.1.2 Improved efficiency due to increased monitorability
                    5.2.1.3 Increased productivity and quicker AI implementation
           5.2.2 RESTRAINTS
                    5.2.2.1 Lack of expertise among personnel
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Expanded use of machine learning in financial sector
           5.2.4 CHALLENGES
                    5.2.4.1 Difficulty in managing various pipelines
                    5.2.4.2 Risk of raw data manipulation
    5.3 MLOPS MARKET: KEY PHASES 
           FIGURE 21 MARKET: KEY PHASES
    5.4 MARKET: ARCHITECTURE 
           FIGURE 22 MLOPS MARKET: ARCHITECTURE
    5.5 MARKET: VALUE CHAIN ANALYSIS 
           FIGURE 23 MARKET: VALUE CHAIN
    5.6 ECOSYSTEM 
           FIGURE 24 MARKET: ECOSYSTEM
           TABLE 6 MARKET: ECOSYSTEM
    5.7 MLOPS CAPABILITIES 
           5.7.1 EXPLORATORY DATA ANALYSIS
           5.7.2 DATA PREP AND FEATURE ENGINEERING
           5.7.3 MODEL TRAINING AND TUNING
           5.7.4 MODEL REVIEW AND GOVERNANCE
           5.7.5 MODEL INFERENCE AND SERVING
           5.7.6 MODEL MONITORING
           5.7.7 AUTOMATED MODEL RETRAINING
    5.8 PRICING MODELS OF MLOPS MARKET PLAYERS 
           TABLE 7 PRICING MODELS AND INDICATIVE PRICE POINTS, 2021–2022
    5.9 TECHNOLOGY ANALYSIS 
           5.9.1 INTRODUCTION
           5.9.2 ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
    5.10 CASE STUDY ANALYSIS 
           5.10.1 EXTERNAL SOLUTION SIMPLIFIES MACHINE LEARNING INFRASTRUCTURE AUTOMATION
           5.10.2 COMPOSITE+ INCREASES ACCURACY OF BOND PRICE PREDICTION
           5.10.3 CLEARML SOLUTION ENABLES EFFICIENT AGRICULTURAL IMAGERY ANALYSIS
           5.10.4 CONTINUUM INDUSTRIES COLLABORATES WITH NEPTUNE.AI TO INTEGRATE MLOPS SOLUTION IN CORE PRODUCT
           5.10.5 JANSSEN PHARMACEUTICALS ACHIEVES FASTER DEEP LEARNING MODEL DEVELOPMENT WITH DOMINO DATA LAB’S MLOPS SOLUTION
    5.11 PATENT ANALYSIS 
           5.11.1 METHODOLOGY
           5.11.2 PATENT DOCUMENT TYPES
                    TABLE 8 PATENTS FILED, 2019–2022
           5.11.3 INNOVATION AND PATENT APPLICATIONS
                    FIGURE 25 TOTAL NUMBER OF PATENTS GRANTED PER YEAR, 2019–2022
                    5.11.3.1 Top applicants
                               FIGURE 26 TOP TEN COMPANIES WITH HIGHEST NUMBER OF PATENT APPLICATIONS, 2019–2022
                               TABLE 9 US: TOP TEN PATENT OWNERS IN MLOPS MARKET, 2019–2022
                               TABLE 10 PATENTS IN MARKET,  2020–2022
    5.12 PORTER’S FIVE FORCES ANALYSIS 
                    TABLE 11 MARKET: PORTER’S FIVE FORCES MODEL
           5.12.1 THREAT OF NEW ENTRANTS
           5.12.2 THREAT OF SUBSTITUTES
           5.12.3 BARGAINING POWER OF SUPPLIERS
           5.12.4 BARGAINING POWER OF BUYERS
           5.12.5 INTENSITY OF COMPETITIVE RIVALRY
    5.13 KEY STAKEHOLDERS AND BUYING CRITERIA 
           5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
                    FIGURE 27 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS  FOR TOP THREE END USERS
                    TABLE 12 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END USERS (%)
           5.13.2 BUYING CRITERIA
                    FIGURE 28 KEY BUYING CRITERIA FOR TOP THREE END USERS
                    TABLE 13 KEY BUYING CRITERIA FOR TOP THREE VERTICALS
    5.14 REGULATORY LANDSCAPE 
           5.14.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
                    TABLE 14 NORTH AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES,  AND OTHER ORGANIZATIONS
                    TABLE 15 EUROPE: REGULATORY BODIES, GOVERNMENT AGENCIES,  AND OTHER ORGANIZATIONS
                    TABLE 16 ASIA PACIFIC: REGULATORY BODIES, GOVERNMENT AGENCIES,  AND OTHER ORGANIZATIONS
                    TABLE 17 MIDDLE EAST & AFRICA: REGULATORY BODIES, GOVERNMENT AGENCIES,  AND OTHER ORGANIZATIONS
                    TABLE 18 LATIN AMERICA: REGULATORY BODIES, GOVERNMENT AGENCIES,  AND OTHER ORGANIZATIONS
                    5.14.1.1 North America
                               5.14.1.1.1 US
                               5.14.1.1.2 Canada
                    5.14.1.2 Europe
                               5.14.1.2.1 General Data Protection Regulation
                               5.14.1.2.2 European Committee for Standardization (CEN)
                               5.14.1.2.3 European Technical Standards Institute (ETSI)
                    5.14.1.3 Asia Pacific
                               5.14.1.3.1 China
                               5.14.1.3.2 India
                               5.14.1.3.3 Australia
                               5.14.1.3.4 Japan
                    5.14.1.4 Middle East & Africa
                               5.14.1.4.1 Middle East
                               5.14.1.4.2 South Africa
                    5.14.1.5 Latin America
                               5.14.1.5.1 Brazil
                               5.14.1.5.2 Mexico
    5.15 KEY CONFERENCES & EVENTS, 2022–2023 
                    TABLE 19 MLOPS MARKET: CONFERENCES & EVENTS
 
6 MLOPS MARKET, BY COMPONENT (Page No. - 74)
    6.1 INTRODUCTION 
           6.1.1 COMPONENT: MARKET DRIVERS
                    FIGURE 29 PLATFORMS SEGMENT TO ACCOUNT FOR LARGER MARKET SIZE DURING FORECAST PERIOD
                    TABLE 20 MLOPS MARKET, BY COMPONENT, 2018–2021 (USD MILLION)
                    TABLE 21 MLOPS MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
    6.2 PLATFORMS 
           6.2.1 OFFER FLEXIBILITY TO DATA MANAGEMENT TEAMS
                    TABLE 22 PLATFORMS: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 23 PLATFORMS: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    6.3 SERVICES 
           6.3.1 PROVIDE READY-TO-DEPLOY SOLUTIONS FOR MANAGING DATA AND TRAINING ML MODELS
                    TABLE 24 SERVICES: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 25 SERVICES: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
           6.3.2 CONSULTING
                    TABLE 26 CONSULTING: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 27 CONSULTING SERVICES: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
           6.3.3 DEPLOYMENT & INTEGRATION
                    TABLE 28 DEPLOYMENT & INTEGRATION: MLOPS MARKET,  BY REGION, 2018–2021 (USD MILLION)
                    TABLE 29 DEPLOYMENT & INTEGRATION: MLOPS MARKET,  BY REGION, 2022–2027 (USD MILLION)
           6.3.4 SUPPORT & MAINTENANCE
                    TABLE 30 SUPPORT & MAINTENANCE: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 31 SUPPORT & MAINTENANCE: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
 
7 MLOPS MARKET, BY DEPLOYMENT MODE (Page No. - 82)
    7.1 INTRODUCTION 
           7.1.1 DEPLOYMENT MODE: MLOPS MARKET DRIVERS
                    FIGURE 30 ON-PREMISES SEGMENT TO RECORD HIGHER CAGR DURING FORECAST PERIOD
                    TABLE 32 MLOPS MARKET, BY DEPLOYMENT MODE, 2018–2021 (USD MILLION)
                    TABLE 33 MLOPS MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
    7.2 ON-PREMISES 
           7.2.1 OFFERS ENHANCED SECURITY AT LOWER COST
                    TABLE 34 ON-PREMISES: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 35 ON-PREMISES: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    7.3 CLOUD 
           7.3.1 REDUCES OPERATIONAL COSTS AND PROVIDES SCALABILITY
                    TABLE 36 CLOUD: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 37 CLOUD: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
 
8 MLOPS MARKET, BY ORGANIZATION SIZE (Page No. - 87)
    8.1 INTRODUCTION 
           8.1.1 ORGANIZATION SIZE: MLOPS MARKET DRIVERS
                    FIGURE 31 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO RECORD HIGHER CAGR DURING FORECAST PERIOD
                    TABLE 38 MLOPS MARKET, BY ORGANIZATION SIZE, 2018–2021 (USD MILLION)
                    TABLE 39 MLOPS MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
    8.2 SMALL AND MEDIUM-SIZED ENTERPRISES 
           8.2.1 HIGHER ADOPTION OF MLOPS TECHNOLOGY EXPECTED
                    TABLE 40 SMALL AND MEDIUM-SIZED ENTERPRISES: MLOPS MARKET, BY REGION,  2018–2021 (USD MILLION)
                    TABLE 41 SMALL AND MEDIUM-SIZED ENTERPRISES: MLOPS MARKET, BY REGION,  2022–2027 (USD MILLION)
    8.3 LARGE ENTERPRISES 
           8.3.1 GROWING USE OF MLOPS PLATFORMS TO FACILITATE DATA MANAGEMENT
                    TABLE 42 LARGE ENTERPRISES: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 43 LARGE ENTERPRISES: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
 
9 MLOPS MARKET, BY VERTICAL (Page No. - 92)
    9.1 INTRODUCTION 
           9.1.1 VERTICAL: MLOPS DRIVERS
                    FIGURE 32 BFSI SEGMENT TO ACCOUNT FOR LARGEST MARKET SIZE BY 2027
                    TABLE 44 MLOPS MARKET, BY VERTICAL, 2018–2021 (USD MILLION)
                    TABLE 45 MLOPS MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
    9.2 BANKING, FINANCIAL SERVICES, AND INSURANCE 
           9.2.1 MLOPS FACILITATES REAL-TIME FRAUD DETECTION
                    TABLE 46 BANKING, FINANCIAL SERVICES, AND INSURANCE: MLOPS MARKET, BY REGION,  2018–2021 (USD MILLION)
                    TABLE 47 BANKING, FINANCIAL SERVICES, AND INSURANCE: MLOPS MARKET, BY REGION,  2022–2027 (USD MILLION)
    9.3 TELECOM 
           9.3.1 GROWING ADOPTION OF MLOPS TO ENHANCE CUSTOMER ENGAGEMENT
                    TABLE 48 TELECOM: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 49 TELECOM: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    9.4 HEALTHCARE & LIFE SCIENCES 
           9.4.1 IMPROVED DIAGNOSTIC ACCURACY AND RISK ASSESSMENT
                    TABLE 50 HEALTHCARE & LIFE SCIENCES: MLOPS MARKET, BY REGION,  2018–2021 (USD MILLION)
                    TABLE 51 HEALTHCARE & LIFE SCIENCES: MLOPS MARKET,  BY REGION, 2022–2027 (USD MILLION)
    9.5 RETAIL & ECOMMERCE 
           9.5.1 USE OF MLOPS HELPS TAILOR PERSONALIZED EXPERIENCE FOR CONSUMERS
                    TABLE 52 RETAIL & ECOMMERCE: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 53 RETAIL & ECOMMERCE: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    9.6 IT & ITES 
           9.6.1 INCREASED PREFERENCE FOR MLOPS TO MANAGE BIG DATA
                    TABLE 54 IT & ITES: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 55 IT & ITES: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    9.7 GOVERNMENT & DEFENSE 
           9.7.1 USE OF MLOPS TO SOLVE COMPLEX PROBLEMS
                    TABLE 56 GOVERNMENT & DEFENSE: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 57 GOVERNMENT & DEFENSE: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    9.8 MANUFACTURING 
           9.8.1 GROWING ADOPTION OF MLOPS TO OPTIMIZE PLANT PRODUCTION
                    TABLE 58 MANUFACTURING: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 59 MANUFACTURING: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    9.9 ENERGY & UTILITIES 
           9.9.1 NEED FOR MLOPS SOLUTIONS TO ENHANCE EFFICIENCY AND REDUCE WASTE
                    TABLE 60 ENERGY & UTILITIES: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 61 ENERGY & UTILITIES: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
    9.10 TRANSPORTATION & LOGISTICS 
           9.10.1 RISING ADOPTION OF MLOPS TO IMPROVE WAREHOUSE MANAGEMENT AND SUPPLY CHAIN EFFICIENCY
                    TABLE 62 TRANSPORTATION & LOGISTICS: MLOPS MARKET, BY REGION,  2018–2021 (USD MILLION)
                    TABLE 63 TRANSPORTATION & LOGISTICS: MLOPS MARKET, BY REGION,  2022–2027 (USD MILLION)
    9.11 OTHERS (MEDIA & ENTERTAINMENT, TRAVEL & HOSPITALITY,  AND EDUCATION & RESEARCH) 
           9.11.1 INCREASING DEMAND FOR MLOPS TO IMPROVE CUSTOMER EXPERIENCE
                    TABLE 64 OTHERS: MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
                    TABLE 65 OTHERS: MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
 
10 MLOPS MARKET, BY REGION (Page No. - 106)
     10.1 INTRODUCTION 
               FIGURE 33 THAILAND TO ACCOUNT FOR HIGHEST CAGR DURING FORECAST PERIOD
               FIGURE 34 ASIA PACIFIC TO RECORD HIGHEST CAGR DURING FORECAST PERIOD
               TABLE 66 MLOPS MARKET, BY REGION, 2018–2021 (USD MILLION)
               TABLE 67 MLOPS MARKET, BY REGION, 2022–2027 (USD MILLION)
     10.2 NORTH AMERICA 
             10.2.1 NORTH AMERICA: MLOPS MARKET DRIVERS
             10.2.2 NORTH AMERICA: REGULATIONS
                       10.2.2.1 Personal Information Protection and Electronic Documents Act (PIPEDA)
                       10.2.2.2 Gramm–Leach–Bliley Act
                       10.2.2.3 Federal Information Security Management Act
                       10.2.2.4 Health Insurance Portability and Accountability Act of 1996
                       10.2.2.5 Occupational Safety and Health Administration (OSHA)
                       10.2.2.6 California Consumer Privacy Act
                                   FIGURE 35 NORTH AMERICA: MARKET SNAPSHOT
                                   TABLE 68 NORTH AMERICA: MLOPS MARKET, BY COMPONENT, 2018–2021 (USD MILLION)
                                   TABLE 69 NORTH AMERICA: MLOPS MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
                                   TABLE 70 NORTH AMERICA: MLOPS MARKET, BY SERVICE, 2018–2021 (USD MILLION)
                                   TABLE 71 NORTH AMERICA: MLOPS MARKET, BY SERVICE, 2022–2027 (USD MILLION)
                                   TABLE 72 NORTH AMERICA: MLOPS MARKET, BY DEPLOYMENT MODE, 2018–2021 (USD MILLION)
                                   TABLE 73 NORTH AMERICA: MLOPS MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
                                   TABLE 74 NORTH AMERICA: MLOPS MARKET, BY ORGANIZATION SIZE, 2018–2021 (USD MILLION)
                                   TABLE 75 NORTH AMERICA: MLOPS MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
                                   TABLE 76 NORTH AMERICA: MLOPS MARKET, BY VERTICAL, 2018–2021 (USD MILLION)
                                   TABLE 77 NORTH AMERICA: MLOPS MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
                                   TABLE 78 NORTH AMERICA: MLOPS MARKET, BY COUNTRY, 2018–2021 (USD MILLION)
                                   TABLE 79 NORTH AMERICA: MLOPS MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
             10.2.3 US
                       10.2.3.1 Rising demand for automation to streamline business operations to drive MLOps adoption
             10.2.4 CANADA
                       10.2.4.1 Increasing R&D in advanced technologies to boost market
     10.3 EUROPE 
             10.3.1 EUROPE: MLOPS MARKET DRIVERS
             10.3.2 EUROPE: REGULATIONS
                       10.3.2.1 European Market Infrastructure Regulation
                       10.3.2.2 General Data Protection Regulation
                       10.3.2.3 European Committee for Standardization
                       10.3.2.4 European Technical Standards Institute
                                   TABLE 80 EUROPE: MLOPS MARKET, BY COMPONENT, 2018–2021 (USD MILLION)
                                   TABLE 81 EUROPE: MLOPS MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
                                   TABLE 82 EUROPE: MLOPS MARKET, BY SERVICE, 2018–2021 (USD MILLION)
                                   TABLE 83 EUROPE: MLOPS MARKET, BY SERVICE, 2022–2027 (USD MILLION)
                                   TABLE 84 EUROPE: MLOPS MARKET, BY DEPLOYMENT MODE, 2018–2021 (USD MILLION)
                                   TABLE 85 EUROPE: MLOPS MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
                                   TABLE 86 EUROPE: MLOPS MARKET, BY ORGANIZATION SIZE, 2018–2021 (USD MILLION)
                                   TABLE 87 EUROPE: MLOPS MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
                                   TABLE 88 EUROPE: MLOPS MARKET, BY VERTICAL, 2018–2021 (USD MILLION)
                                   TABLE 89 EUROPE: MLOPS MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
                                   TABLE 90 EUROPE: MLOPS MARKET, BY COUNTRY, 2018–2021 (USD MILLION)
                                   TABLE 91 EUROPE: MLOPS MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
             10.3.3 UK
                       10.3.3.1 Growing government initiatives to promote research in AI
             10.3.4 GERMANY
                       10.3.4.1 Increasing popularity of AI solutions across verticals to boost MLOps market
             10.3.5 FRANCE
                       10.3.5.1 Large client base and significant R&D activity to drive market
             10.3.6 REST OF EUROPE
     10.4 ASIA PACIFIC 
             10.4.1 ASIA PACIFIC: MLOPS MARKET DRIVERS
             10.4.2 ASIA PACIFIC: REGULATIONS
                       10.4.2.1 Privacy Commissioner for Personal Data
                       10.4.2.2 Act on the Protection of Personal Information
                       10.4.2.3 Critical Information Infrastructure
                       10.4.2.4 International Organization for Standardization 27001
                       10.4.2.5 Personal Data Protection Act
                                   FIGURE 36 ASIA PACIFIC: MARKET SNAPSHOT
                                   TABLE 92 ASIA PACIFIC: MLOPS MARKET, BY COMPONENT, 2018–2021 (USD MILLION)
                                   TABLE 93 ASIA PACIFIC: MLOPS MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
                                   TABLE 94 ASIA PACIFIC: MLOPS MARKET, BY SERVICE, 2018–2021 (USD MILLION)
                                   TABLE 95 ASIA PACIFIC: MLOPS MARKET, BY SERVICE, 2022–2027 (USD MILLION)
                                   TABLE 96 ASIA PACIFIC: MLOPS MARKET, BY DEPLOYMENT MODE, 2018–2021 (USD MILLION)
                                   TABLE 97 ASIA PACIFIC: MLOPS MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
                                   TABLE 98 ASIA PACIFIC: MLOPS MARKET, BY ORGANIZATION SIZE, 2018–2021 (USD MILLION)
                                   TABLE 99 ASIA PACIFIC: MLOPS MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
                                   TABLE 100 ASIA PACIFIC: MLOPS MARKET, BY VERTICAL, 2018–2021 (USD MILLION)
                                   TABLE 101 ASIA PACIFIC: MLOPS MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
                                   TABLE 102 ASIA PACIFIC: MLOPS MARKET, BY COUNTRY, 2018–2021 (USD MILLION)
                                   TABLE 103 ASIA PACIFIC: MLOPS MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
             10.4.3 CHINA
                       10.4.3.1 Untapped MLOps opportunities across manufacturing industries to impact market
             10.4.4 JAPAN
                       10.4.4.1 Governmental initiatives and strong focus on AI to drive market
             10.4.5 THAILAND
                       10.4.5.1 Digital infrastructure development projects to drive market growth
             10.4.6 MYANMAR
                       10.4.6.1 Growing public sector cloud adoption to boost market
             10.4.7 VIETNAM
                       10.4.7.1 High demand from telecom and manufacturing sectors to impact market
             10.4.8 INDIA
                       10.4.8.1 Growing number of MLOps startups and initiatives to propel market growth
             10.4.9 REST OF ASIA PACIFIC
     10.5 MIDDLE EAST & AFRICA 
             10.5.1 MIDDLE EAST & AFRICA: MLOPS MARKET DRIVERS
             10.5.2 MIDDLE EAST & AFRICA: REGULATIONS
                       10.5.2.1 Israeli Privacy Protection Regulations (Data Security), 5777-2017
                       10.5.2.2 Cloud Computing Framework
                       10.5.2.3 GDPR Applicability in the Kingdom of Saudi Arabia (KSA)
                       10.5.2.4 Protection of Personal Information Act
                                   TABLE 104 MIDDLE EAST & AFRICA: MLOPS MARKET, BY COMPONENT, 2018–2021 (USD MILLION)
                                   TABLE 105 MIDDLE EAST & AFRICA: MLOPS MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
                                   TABLE 106 MIDDLE EAST & AFRICA: MLOPS MARKET, BY SERVICE, 2018–2021 (USD MILLION)
                                   TABLE 107 MIDDLE EAST & AFRICA: MLOPS MARKET, BY SERVICE, 2022–2027 (USD MILLION)
                                   TABLE 108 MIDDLE EAST & AFRICA: MLOPS MARKET, BY DEPLOYMENT MODE,  2018–2021 (USD MILLION)
                                   TABLE 109 MIDDLE EAST & AFRICA: MLOPS MARKET, BY DEPLOYMENT MODE,  2022–2027 (USD MILLION)
                                   TABLE 110 MIDDLE EAST & AFRICA: MLOPS MARKET, BY ORGANIZATION SIZE, 2018–2021 (USD MILLION)
                                   TABLE 111 MIDDLE EAST & AFRICA: MLOPS MARKET, BY ORGANIZATION SIZE,  2022–2027 (USD MILLION)
                                   TABLE 112 MIDDLE EAST & AFRICA: MLOPS MARKET, BY VERTICAL, 2018–2021 (USD MILLION)
                                   TABLE 113 MIDDLE EAST & AFRICA: MLOPS MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
                                   TABLE 114 MIDDLE EAST & AFRICA: MLOPS MARKET, BY COUNTRY, 2018–2021 (USD MILLION)
                                   TABLE 115 MIDDLE EAST & AFRICA: MLOPS MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
             10.5.3 MIDDLE EAST
                       10.5.3.1 Rising demand for innovative technologies to impact market
             10.5.4 SOUTH AFRICA
                       10.5.4.1 Government measures to create awareness of advanced technologies to boost demand for MLOps
             10.5.5 REST OF MIDDLE EAST & AFRICA
     10.6 LATIN AMERICA 
             10.6.1 LATIN AMERICA: MLOPS MARKET DRIVERS
             10.6.2 LATIN AMERICA: REGULATIONS
                       10.6.2.1 Brazil Data Protection Law
                                   TABLE 116 LATIN AMERICA: MLOPS MARKET, BY COMPONENT, 2018–2021 (USD MILLION)
                                   TABLE 117 LATIN AMERICA: MLOPS MARKET, BY COMPONENT, 2022–2027 (USD MILLION)
                                   TABLE 118 LATIN AMERICA: MLOPS MARKET, BY SERVICE, 2018–2021 (USD MILLION)
                                   TABLE 119 LATIN AMERICA: MLOPS MARKET, BY SERVICE, 2022–2027 (USD MILLION)
                                   TABLE 120 LATIN AMERICA: MLOPS MARKET, BY DEPLOYMENT MODE, 2018–2021 (USD MILLION)
                                   TABLE 121 LATIN AMERICA: MLOPS MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD MILLION)
                                   TABLE 122 LATIN AMERICA: MLOPS MARKET, BY ORGANIZATION SIZE, 2018–2021 (USD MILLION)
                                   TABLE 123 LATIN AMERICA: MLOPS MARKET, BY ORGANIZATION SIZE, 2022–2027 (USD MILLION)
                                   TABLE 124 LATIN AMERICA: MLOPS MARKET, BY VERTICAL, 2018–2021 (USD MILLION)
                                   TABLE 125 LATIN AMERICA: MLOPS MARKET, BY VERTICAL, 2022–2027 (USD MILLION)
                                   TABLE 126 LATIN AMERICA: MLOPS MARKET, BY COUNTRY, 2018–2021 (USD MILLION)
                                   TABLE 127 LATIN AMERICA: MLOPS MARKET, BY COUNTRY, 2022–2027 (USD MILLION)
             10.6.3 BRAZIL
                       10.6.3.1 Security and theft protection regulations to drive market growth
             10.6.4 MEXICO
                       10.6.4.1 Government support for adoption of emerging technologies to drive demand for MLOps
             10.6.5 REST OF LATIN AMERICA
 
11 COMPETITIVE LANDSCAPE (Page No. - 144)
     11.1 OVERVIEW 
     11.2 STRATEGIES OF KEY PLAYERS 
               TABLE 128 OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN MLOPS MARKET
     11.3 REVENUE ANALYSIS 
               FIGURE 37 REVENUE ANALYSIS FOR KEY COMPANIES, 2018?2021
     11.4 MARKET SHARE ANALYSIS 
               FIGURE 38 MLOPS MARKET SHARE ANALYSIS FOR KEY PLAYERS IN 2022
               TABLE 129 MLOPS MARKET: DEGREE OF COMPETITION
     11.5 COMPANY EVALUATION QUADRANT 
             11.5.1 STARS
             11.5.2 EMERGING LEADERS
             11.5.3 PERVASIVE PLAYERS
             11.5.4 PARTICIPANTS
                       FIGURE 39 KEY MLOPS MARKET PLAYERS, COMPANY EVALUATION MATRIX, 2022
     11.6 STARTUP/SME EVALUATION MATRIX 
             11.6.1 PROGRESSIVE COMPANIES
             11.6.2 RESPONSIVE COMPANIES
             11.6.3 DYNAMIC COMPANIES
             11.6.4 STARTING BLOCKS
                       FIGURE 40 MLOPS MARKET EVALUATION MATRIX FOR STARTUPS/SMES, 2022
     11.7 COMPETITIVE BENCHMARKING 
               TABLE 130 MLOPS MARKET: KEY STARTUPS/SMES
               TABLE 131 MLOPS MARKET: COMPETITIVE BENCHMARKING OF KEY PLAYERS (STARTUPS/SMES)
               TABLE 132 MLOPS MARKET: COMPETITIVE BENCHMARKING OF KEY PLAYERS (STARTUPS/SMES)
     11.8 COMPETITIVE SCENARIO 
             11.8.1 PRODUCT LAUNCHES
                       TABLE 133 PRODUCT LAUNCHES, 2018–2022
             11.8.2 DEALS
                       TABLE 134 DEALS, 2018–2022
             11.8.3 OTHERS
                       TABLE 135 OTHERS, 2019–2020
 
12 COMPANY PROFILES (Page No. - 156)
     12.1 MAJOR PLAYERS 
(Business Overview, Products, Solutions & Services offered, Recent Developments, MnM View)*
             12.1.1 HPE
                       TABLE 136 HPE: BUSINESS OVERVIEW
                       FIGURE 41 HPE: FINANCIAL OVERVIEW
                       TABLE 137 HPE: PRODUCTS OFFERED
                       TABLE 138 HPE: PRODUCT LAUNCHES
                       TABLE 139 HPE: DEALS
             12.1.2 IBM
                       TABLE 140 IBM: BUSINESS OVERVIEW
                       FIGURE 42 IBM: FINANCIAL OVERVIEW
                       TABLE 141 IBM: PRODUCTS OFFERED
                       TABLE 142 IBM: PRODUCT LAUNCHES
                       TABLE 143 IBM: DEALS
             12.1.3 ALTERYX
                       TABLE 144 ALTERYX: BUSINESS OVERVIEW
                       FIGURE 43 ALTERYX: FINANCIAL OVERVIEW
                       TABLE 145 ALTERYX: PRODUCTS OFFERED
                       TABLE 146 ALTERYX: PRODUCT LAUNCHES
                       TABLE 147 ALTERYX: DEALS
                       TABLE 148 ALTERYX: OTHERS
             12.1.4 GOOGLE
                       TABLE 149 GOOGLE: BUSINESS OVERVIEW
                       FIGURE 44 GOOGLE: COMPANY SNAPSHOT
                       TABLE 150 GOOGLE: PRODUCTS OFFERED
                       TABLE 151 GOOGLE: PRODUCT LAUNCHES AND ENHANCEMENTS
                       TABLE 152 GOOGLE: DEALS
             12.1.5 GAVS TECHNOLOGIES
                       TABLE 153 GAVS TECHNOLOGIES: BUSINESS OVERVIEW
                       TABLE 154 GAVS TECHNOLOGIES: PRODUCTS OFFERED
                       TABLE 155 GAVS TECHNOLOGIES: DEALS
             12.1.6 DATAROBOT
                       TABLE 156 DATAROBOT: BUSINESS OVERVIEW
                       TABLE 157 DATAROBOT: PRODUCTS OFFERED
                       TABLE 158 DATAROBOT: PRODUCT LAUNCHES AND ENHANCEMENTS
                       TABLE 159 DATAROBOT: DEALS
             12.1.7 CLOUDERA
                       TABLE 160 CLOUDERA
                       TABLE 161 CLOUDERA: PRODUCTS OFFERED
                       TABLE 162 CLOUDERA: PRODUCT LAUNCHES AND ENHANCEMENTS
                       TABLE 163 CLOUDERA: DEALS
             12.1.8 AWS
                       TABLE 164 AWS: BUSINESS OVERVIEW
                       FIGURE 45 AWS: COMPANY SNAPSHOT
                       TABLE 165 AWS: PRODUCTS OFFERED
                       TABLE 166 AWS: PRODUCT LAUNCHES AND ENHANCEMENTS
                       TABLE 167 AWS: DEALS
*Details on Business Overview, Solutions, Products & Services offered, Recent Developments, MnM View might not be captured in case of unlisted companies.
     12.2 STARTUPS/SMES 
             12.2.1 DOMINO DATA LAB
             12.2.2 VALOHAI
             12.2.3 H2O.AI
             12.2.4 MLFLOW
             12.2.5 NEPTUNE.AI
             12.2.6 COMET
             12.2.7 SPARKCOGNITION
             12.2.8 HOPSWORKS
             12.2.9 DATATRON
             12.2.10 WEIGHTS & BIASES
             12.2.11 KATONIC.AI
             12.2.12 MODZY
             12.2.13 IGUAZIO
             12.2.14 TELIOLABS
             12.2.15 CLEARML
             12.2.16 AKIRA.AI
             12.2.17 BLAIZE
 
13 ADJACENT AND RELATED MARKETS (Page No. - 201)
     13.1 INTRODUCTION 
     13.2 ARTIFICIAL INTELLIGENCE MARKET – GLOBAL FORECAST TO 2027 
             13.2.1 MARKET DEFINITION
             13.2.2 MARKET OVERVIEW
             13.2.3 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING
                       TABLE 168 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2016–2021 (USD BILLION)
                       TABLE 169 ARTIFICIAL INTELLIGENCE MARKET, BY OFFERING, 2022–2027 (USD BILLION)
             13.2.4 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY
                       TABLE 170 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2016–2021 (USD BILLION)
                       TABLE 171 ARTIFICIAL INTELLIGENCE MARKET, BY TECHNOLOGY, 2022–2027 (USD BILLION)
             13.2.5 ARTIFICIAL INTELLIGENCE MARKET, BY DEPLOYMENT MODE
                       TABLE 172 ARTIFICIAL INTELLIGENCE MARKET, BY DEPLOYMENT MODE, 2016–2021 (USD BILLION)
                       TABLE 173 ARTIFICIAL INTELLIGENCE MARKET, BY DEPLOYMENT MODE, 2022–2027 (USD BILLION)
             13.2.6 ARTIFICIAL INTELLIGENCE MARKET, BY ORGANIZATION SIZE
                       TABLE 174 ARTIFICIAL INTELLIGENCE MARKET, BY ORGANIZATION, 2016–2021 (USD BILLION)
                       TABLE 175 ARTIFICIAL INTELLIGENCE MARKET, BY ORGANIZATION, 2022–2027 (USD BILLION)
             13.2.7 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION
                       TABLE 176 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2016–2021 (USD BILLION)
                       TABLE 177 ARTIFICIAL INTELLIGENCE MARKET, BY BUSINESS FUNCTION, 2022–2027 (USD BILLION)
             13.2.8 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL
                       TABLE 178 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2016–2021 (USD BILLION)
                       TABLE 179 ARTIFICIAL INTELLIGENCE MARKET, BY VERTICAL, 2022–2027 (USD BILLION)
             13.2.9 ARTIFICIAL INTELLIGENCE MARKET, BY REGION
                       TABLE 180 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2016–2021 (USD BILLION)
                       TABLE 181 ARTIFICIAL INTELLIGENCE MARKET, BY REGION, 2022–2027 (USD BILLION)
     13.3 AI GOVERNANCE MARKET – GLOBAL FORECAST TO 2026 
             13.3.1 MARKET DEFINITION
             13.3.2 MARKET OVERVIEW
             13.3.3 AI GOVERNANCE MARKET, BY COMPONENT
                       TABLE 182 AI GOVERNANCE MARKET SIZE, BY COMPONENT, 2020–2026 (USD MILLION)
             13.3.4 AI GOVERNANCE MARKET, BY DEPLOYMENT MODE
                       TABLE 183 AI GOVERNANCE MARKET SIZE, BY DEPLOYMENT MODE, 2020–2026 (USD MILLION)
             13.3.5 AI GOVERNANCE MARKET, BY ORGANIZATION SIZE
                       TABLE 184 AI GOVERNANCE MARKET SIZE, BY ORGANIZATION SIZE, 2020–2026 (USD MILLION)
             13.3.6 AI GOVERNANCE MARKET, BY VERTICAL
                       TABLE 185 AI GOVERNANCE MARKET SIZE, BY VERTICAL, 2020–2026 (USD MILLION)
             13.3.7 AI GOVERNANCE MARKET, BY REGION
                       TABLE 186 AI GOVERNANCE MARKET SIZE, BY REGION, 2020–2026 (USD MILLION)
 
14 APPENDIX (Page No. - 211)
     14.1 DISCUSSION GUIDE 
     14.2 KNOWLEDGESTORE: MARKETSANDMARKETS’  SUBSCRIPTION PORTAL 
     14.3 CUSTOMIZATION OPTIONS 
     14.4 RELATED REPORTS 
     14.5 AUTHOR DETAILS 

This research study involved the extensive use of secondary sources, directories, and databases, such as Dun and Bradstreet (D&B), Hoovers, and Bloomberg BusinessWeek, to identify and collect information useful for a technical, market-oriented, and commercial study of the MLOps market. The study involved four major activities in estimating the current size of the MLOps market. Exhaustive secondary research was done to collect information on the MLOps industry. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain using primary research. Both top-down and bottom-up approaches were employed to estimate the overall market size. Thereafter, market breakup and data triangulation procedures were used to estimate the size of the segments and subsegments of the market.

Secondary Research

The market for the companies offering MLOps solutions and services is arrived at based on secondary data available through paid and unpaid sources and by analyzing the product portfolios of the major companies in the ecosystem and rating the companies based on performance and quality. In the secondary research process, various sources were referred to, for identifying and collecting information for this study. The secondary sources include annual reports, press releases and investor presentations of companies, white papers, journals, and certified publications and articles from recognized authors, directories, and databases. Secondary research was used to obtain key information about the industry’s supply chain, the total pool of key players, market classification and segmentation according to the industry trends to the bottom-most level, regional markets, and key developments from both market-and technology-oriented perspectives, all of which were further validated by primary sources.

Primary Research

In the primary research process, various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information for the report. The primary sources from the supply side included Chief Executive Officers (CEOs), Chief Technology Officers (CTOs), Chief Operating Officers (COOs), Vice Presidents (VPs), Managing Directors (MDs), technology and innovation directors, and related key executives from various key companies and organizations operating in the MLOps market. Primary interviews were conducted to gather insights, such as market statistics, data of revenue collected from solutions and services, market breakups, market size estimations, market forecasts, and data triangulation. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Finance Officers (CFOs), Chief Strategy Officers (CSOs), and the installation team of end users who use Connected Toys, were interviewed to understand buyers’ perspectives on suppliers, products, service providers, and their current usage of Connected Toys, which is expected to affect the overall MLOps market growth. Following is the breakup of the primary respondents:

MLOps Market Size, and Share

To know about the assumptions considered for the study, download the pdf brochure

Note: Tier 1 companies have revenues over USD 1 billion; Tier 2 companies’ revenue ranges between USD 500 million and 1 billion; and Tier 3 companies’ revenue ranges between USD 100 million and USD 500 million Others include senior-level managers, sales executives, and independent consultants RoW includes Middle East and Africa and Latin America

Market Size Estimation

Both top-down and bottom-up approaches were used to estimate and validate the total size of the MLOps market. These methods were extensively used to estimate the size of various segments in the market. The research methodology used to estimate the market size includes the following:

  • Key players in the market have been identified through extensive secondary research.
  • The industry’s supply chain and market size have been determined through primary and secondary research processes.
  • All percentage shares, splits, and breakups have been determined using secondary sources and verified through primary sources.

Data Triangulation

After arriving at the overall market size, the overall MLOps market was divided into several segments and subsegments. The data triangulation procedures were used to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments. The data was triangulated by studying various factors and trends from the demand and supply sides. Along with data triangulation and market breakdown, the market size was validated by the top-down and bottom-up approaches.

Report Objectives

  • To determine, segment, and forecast the global MLOps market based on component, application, organization size, deployment type, vertical, and region
  • To forecast the size of the market segments with respect to five main regions: North America, Europe, Asia Pacific (APAC), Latin America, and Middle East and Africa (MEA)
  • To provide detailed information about the major factors (drivers, opportunities, threats, and challenges) influencing the growth of the market
  • To study the complete value chain and related industry segments and perform a value chain analysis of the market landscape
  • To strategically analyze macro and micromarkets1 with respect to individual growth trends, prospects, and contributions to the total market
  • To analyze industry trends, pricing data, and patents and innovations related to the market
  • To analyze opportunities in the market for stakeholders by identifying the high-growth segments of the MLOps market

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Geographic Analysis

  • Further breakup of the Asia Pacific market into countries contributing 75% to the regional market size
  • Further breakup of the North American market into countries contributing 75% to the regional market size
  • Further breakup of the Latin American market into countries contributing 75% to the regional market size
  • Further breakup of the MEA market into countries contributing 75% to the regional market size
  • Further breakup of the European market into countries contributing 75% to the regional market size

Company Information

  • Detailed analysis and profiling of additional market players (up to 5)
Report Code
TC 8518
Published ON
Dec, 2022
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