The no-code machine learning 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.
No-Code Machine Learning 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 no-code machine learning market size has grown exponentially in recent years. It will grow from $0.85 billion in 2023 to $1.10 billion in 2024 at a compound annual growth rate (CAGR) of 30.3%. The growth in the historic period can be attributed to increasing demand for user-friendly tools, rise in need for cost-effective machine learning solutions, increasing use of cloud-based no-code platforms, increasing awareness of machine learning benefits among non-technical users, and rise in popularity of low-code and no-code platforms.
The no-code machine learning market size is expected to see exponential growth in the next few years. It will grow to $3.22 billion in 2028 at a compound annual growth rate (CAGR) of 30.7%. The growth in the forecast period can be attributed to rising demand for accessible AI tools, rising adoption of AI across various sectors, growing adoption of cloud computing, increasing availability of pre-built machine learning templates, and growing focus on reducing the technical skills barrier. Major trends in the forecast period include technological advancements, AI-driven personalization, IoT applications, predictive analytics, and self-service analytics.
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Scope Of No-Code Machine Learning 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.
No-Code Machine Learning Market Overview
Market Drivers –
The rising adoption of the internet of things (IoT) is expected to propel the growth of the no-code machine learning market going forward. The Internet of Things (IoT) refers to the network of interconnected devices and systems that communicate and exchange data with each other over the Internet to automate processes and enhance operational efficiency. The adoption of IoT is due to its ability to improve operational efficiency, provide real-time data insights, enable automation and remote monitoring, reduce costs, improve decision-making, and drive innovation across various industries by connecting and optimizing a wide range of devices and systems. No-code machine learning is increasingly being used in the Internet of Things (IoT) to facilitate creating, deploying, and managing machine learning models without deep technical expertise. For instance, in November 2022, according to Ericsson, a Sweden-based network and telecommunications company, the number of global IoT-connected devices is expected to increase from 13.2 billion in 2022 to 34.7 billion by 2028. Therefore, the rise in adoption of the internet of things (IoT) is driving the growth of the no-code machine learning market.
Market Trends —
Major companies operating in the no-code machine learning market are focused on developing advanced technology to improve workflow automation, such as no-code machine learning tools. No-code machine learning tools allow users to create and deploy machine learning models without writing code, making the technology more accessible to non-technical users. For instance, in December 2023, Amazon, a US-based technology company, launched SageMaker Canvas, a no-code machine learning tool designed to enable users without coding experience to build machine learning models. Targeted at business analysts and non-technical users, this tool features a user-friendly interface for easy model creation, data preparation, and training. Critical applications include customer churn prediction, fraud detection, and inventory optimization.
The no-code machine learning market covered in this report is segmented —
1) By Offering: Platform, Services
2) By Deployment Mode: Cloud-Based, On-Premise
3) By Industry Vertical: Banking, Financial Services And Insurance (BFSI), Healthcare, Retail, Information Technology(IT) And Telecom, Manufacturing, Government
4) By Application: Predictive Analytics, Process Automation, Data Visualization, Business Intelligence, Customer Relationship Management, Supply Chain Optimization
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Regional Insights —
North America was the largest region in the no-code machine learning market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the no-code machine learning market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
Key Companies —
Major companies operating in the no-code machine learning market are Apple Create ML, Microsoft Azure Machine Learning Studio, Amazon Web Services, SAS Viya, DataRobot Inc., LityxIQ, H2O.ai, Dataiku DSS, C3 AI Suite, RapidMiner Studio, BigML Inc., Google Teachable Machine, Edge Impulse, Microsoft Lobe, KNIME Analytics Platform, MonkeyLearn, Akkio AI, Obviously AI, Runway ML, Fritz AI, Sway AI, PyCaret, Ever AI, Neural Designer
Table of Contents
1. Executive Summary
2. No-Code Machine Learning Market Report Structure
3. No-Code Machine Learning Market Trends And Strategies
4. No-Code Machine Learning Market — Macro Economic Scenario
5. No-Code Machine Learning Market Size And Growth
…..
27. No-Code Machine Learning Market Competitor Landscape And Company Profiles
28. Key Mergers And Acquisitions
29. Future Outlook and Potential Analysis
30. Appendix
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