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Report Description

Report Description

 

Forecast Period

2024-2028

Market Size (2022)

USD 1.12 Billion

CAGR (2023-2028)

42.48%

Fastest Growing Segment

Manufacturing

Largest Market

North America

 

Global automated machine learning solution market is anticipated to thrive in the forecast period 2023-2028. The usage of predictive lead scoring systems for customer segmentation and targeting potential consumers is rising the demand for the automated machine learning (AutoML) solutions across the globe.

Many areas of the industry now depend heavily on machine learning (ML). On the other hand, developing high-performance machine learning systems requires highly specialised data scientists and subject matter specialists. By enabling domain experts to automatically create machine learning applications without extensive statistical and machine learning skills, automated machine learning (AutoML) aims to reduce the need for data scientists. The advancements in data science and artificial intelligence have improved automated machine learning's performance. Because businesses see this technology's promise, its adoption rate is expected to increase during the projected period. Customers may now employ automated machine learning solutions more easily since businesses are selling them as subscription services. Additionally, it provides pay-as-you-go flexibility.

Machine learning (ML) is being utilised more often in a variety of applications lately, but there aren't enough machine learning professionals to keep up with this increase. The goal of automated machine learning (AutoML) is to make machine learning more approachable. As a result, professionals should be able to install more machine learning systems, and using AutoML would need less skill than using ML directly. The technology's acceptance, nevertheless, is currently only moderate, which limits the global  automated machine learning solution market expansion.

After the COVID-19 epidemic, organisations have been increasingly relying on intelligent solutions to automate their business operations, which is causing a rise in the use of AI. This pattern is anticipated to persist throughout the ensuing years, accelerating the adoption of AI in business operations.

Increasing Demand for Efficient Fraud Detection Solutions

Machine learning is used in a wide range of financial applications, including trading, process automation, credit scoring, and underwriting for loans and insurance. One of the major issues with financial security is financial fraud. Machine learning is currently being used for fraud detection applications to combat the rising danger of financial fraud. In order to make use of the massive data accessible from recently acquired digital channels, several firms in the financial services sector are now actively integrating AI and ML into their ecosystems. A paradigm change in customer behaviour and priorities brought about by the pandemic has also boosted its expansion, leading 54% of financial services companies with more least 5,000 workers to integrate the technology into their business practises. Businesses are increasingly in need of a fraud detection system that can provide real-time and actionable warnings as they progress towards accepting credit card payments online. These factors are driving the global automated machine learning solution market.


Demand for Intelligent Business Processes is Rising

Artificial Intelligence (AI) usage is increasing as businesses now turn to utilising next-generation technology. Businesses may employ artificial intelligence for a variety of purposes, including data collection and work process efficiency. As a result of the widespread use of AI analytics in off-the-shelf CRM platforms, sales teams can now provide insightful data on demand. Salesforce's Einstein AI technology, for instance, can forecast which customers are most likely to increase sales and to switch brands. With information like this, salespeople can concentrate their time and efforts where it counts the most. Additionally, the growing emphasis that businesses are placing on evaluating and improving customer services is fostering the expansion of AI-based processes within organisations. It gives businesses improved understanding of consumer preferences and purchasing trends, which in turn enables them to provide tailored product suggestions. The need for AI is rising as a result of the expanding deployment of robotics across a variety of industries, including manufacturing and warehousing, among others. Co-bots are aware of the people around them because to AI technologies like machine vision. They can respond appropriately, for instance by slowing down or turning around to avoid people. As a result, processes may be created to maximise the capabilities of both people and robots.

Slow Adoption of Automated Machine Learning Tools

Machine learning (ML) is being employed in a growing number of applications, but there aren't enough machine learning specialists to keep up with this expansion. The goal of automated machine learning (AutoML) is to make machine learning more approachable. As a result, specialists should be able to install more machine learning systems, and working with AutoML would need less skill than dealing with ML directly. The technology's acceptance, nevertheless, is currently moderate, which limits the automated machine learning solution market's expansion. First, there is a misconception that AutoML approaches are difficult to use and would demand a substantial initial investment to understand how to utilise them. Secondly, autoML systems occasionally have trouble working with user data but don't always identify the issue.. Concerns were also raised over the amount of processing power needed to use AutoML.

Growing Healthcare Applications

Many applications in the field of healthcare already make use of machine learning technology. This platform analyses millions of different data points from this sector vertical, forecasts results, and also offers rapid risk assessments and precise resource allocation.

The ability to diagnose and identify disorders and illnesses that might occasionally be challenging to recognise is one of this technology's most significant uses in healthcare. This can include a number of inherited conditions and tumours that are challenging to identify in the first stages. The IBM Watson Genomics is a notable illustration of this, demonstrating how genome-based tumour sequencing in conjunction with cognitive computing may facilitate cancer detection.

A major biopharmaceutical company called Berg, uses AI to provide medicinal treatments for diseases like cancer. All these factors are driving the market of global automated machine learning solution market.

Resistance among Users Regarding Automated Machine Learning Solutions

The market's delayed adoption of automated machine learning solutions is mostly due to the limited uptake of machine learning technologies. Companies struggle to obtain the domain experts they need since there is a significant demand for them in the machine learning proper ability. Additionally, because it is expensive to hire these professionals, businesses are even less likely to adopt cutting-edge technology like machine learning. The sorts of end users may also affect the resistance to using AutoML technologies. For instance, given that they manage citizen data, government organisations may show resistance to using automated machine learning solutions. As a result, concerns over privacy and the sensitivity of data may deter them from using such solutions, slowing the market's expansion. Additionally, people are reluctant to utilise such tools due to the limits of the technology, which have been noted by several industry professionals. These are issues with data and model application that AutoML encounters. For instance, inconsistent data during offline data processing and insufficiently high-quality labelled data would have negative impacts. Additionally, teams must do technical-demanding automated machine learning processing of unstructured and semi-structured data.

Market Segmentation

The automated machine learning solution market is segmented into offering, deployment, automation type,  enterprise size, end-users, company, and region. Based on offering, the market is segmented into platform and service. Based on deployment, the market is segmented into on-premise and cloud. Based on automation type, the market is segmented into data processing, feature engineering, modeling, and visualization. Based on enterprise size, the market is segmented into large enterprise and SMEs. Based on end-users, the market is segmented into BFSI, retail and e-commerce, healthcare, and manufacturing. Based on region, the market is segmented into North America, Asia-Pacific, Europe, South America, and Middle East & Africa

Market Players

Some of the major market players in the global automated machine learning solution market are Datarobot Inc., Amazon Web Services Inc., dotData Inc., IBM Corporation, Dataiku, EdgeVerve Systems Limited, Big Squid Inc., SAS Institute Inc., Microsoft Corporation, and Determined.ai Inc.

Recent Developments

  • Meta chose AWS as a significant and a long-term strategic cloud supplier in December 2021. Together, Meta and AWS endeavoured to enhance PyTorch users' performance on AWS and quicken the process by which programmers create, train, deploy, and use AI/ML models.
  • In November 2021, SAS's flagship SAS Viya platform received support for open-source users. SAS Viya is used for open-source utility and integration. The software user built an API-first strategy that supported a machine learning-powered data preparation procedure.
  • Dot Data, a supplier of full-cycle business AI automation solutions, and Tableau, an analytics platform, announced a cooperation in September 2021 to let Tableau users take advantage of dotData's AI Automation Capabilities. Tableau users can perform full-cycle predictive analysis from raw data through data preparation and insight discovery through AI-based predictions and actionable dashboards by combining Tableau's data preparation and visualisation capabilities with dotData's enhanced insights discovery and predictive modelling capabilities.

Attribute

Details

Base Year

2022

Historic Data

2018 – 2021

Estimated Year

2023

Forecast Period

2024 – 2028

Quantitative Units

Revenue in USD Million and CAGR for 2018-2022 and 2024-2028

Report Coverage

Revenue forecast, company share, growth factors, and trends

Segments Covered

Offering

Deployment

Automation Type

Enterprise Size

End-users

Region

Regional Scope

North America; Asia-Pacific; Europe; South America; and Middle East & Africa

Country Scope

United States, Canada, Mexico, China, India, Japan, South Korea, Australia, Singapore, Malaysia, Germany, United Kingdom, France, Russia, Spain, Belgium, Italy, Brazil, Colombia, Argentina, Peru, Chile, Saudi Arabia, South Africa, UAE, Israel, and Turkey

Key Companies Profiled

Datarobot Inc., Amazon Web Services Inc., dotData Inc., IBM Corporation, Dataiku, EdgeVerve Systems Limited, Big Squid Inc., SAS Institute Inc., Microsoft Corporation, and Determined.ai Inc.

Customization Scope

10% free report customization with purchase. Addition or alteration to country, regional & segment scope.

Pricing and Purchase Options

Avail customized purchase options to meet your exact research needs. Explore purchase options

Delivery Format

PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)

Report Scope:

In this report, the global automated machine learning solution market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

  • Automated Machine Learning Solution Market, By Offering

o   Platform

o   Service

  • Automated Machine Learning Solution Market, By Deployment:

o   On-Premise

o   Cloud

  • Automated Machine Learning Solution Market, By Automation Type:

o   Data Processing

o   Feature Engineering

o   Modeling

o   Visualization

  • Automated Machine Learning Solution Market, By Enterprise Size:

o   Large Enterprises

o   SMEs

  • Automated Machine Learning Solution Market, By End-users:

o   BFSI

o   Retail and E-Commerce

o   Healthcare

o   Manufacturing

  • Automated Machine Learning Solution Market, By Region:

o   North America

§  United States

§  Canada

§  Mexico

o   Asia-Pacific

§  India

§  China

§  Japan

§  South Korea

§  Australia

§  Singapore

§  Malaysia

o   Europe

§  Germany

§  United Kingdom

§  France

§  Russia

§  Spain

§  Belgium

§  Italy

o   South America

§  Brazil

§  Argentina

§  Colombia

§  Peru

§  Chile

o   Middle East

§  Saudi Arabia

§  South Africa

§  UAE

§  Israel

§  Turkey

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the global automated machine learning solution market.

Available Customizations:

Global automated machine learning solution market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

The global automated machine learning solution market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

Table of content

1.    Service Overview

2.    Research Methodology

3.    Impact of COVID-19 on Global Automated Machine Learning Solution Market

4.    Executive Summary

5.    Voice of Customers

6.    Global Automated Machine Learning Solution Market Outlook

6.1.  Market Size & Forecast

6.1.1.    By Value

6.2.  Market Share & Forecast

6.2.1.    By Offering( Platform, Service)

6.2.2.    By Deployment (On-Premise, Cloud)

6.2.3.    By Automation Type (Data Processing, Feature Engineering, Modeling, Visualization)

6.2.4.    By Enterprise Size(Large Enterprises, SMEs)

6.2.5.    By End-users (BFSI, Retail and E-Commerce, Healthcare, Manufacturing)

6.2.6.    By Region

6.3.  By Company (2022)

6.4.  Market Map

7.    North America Automated Machine Learning Solution Market Outlook

7.1.  Market Size & Forecast

7.1.1.    By Value

7.2.  Market Share & Forecast

7.2.1.    By Offering

7.2.2.    By Deployment

7.2.3.    By Automation Type

7.2.4.    By Enterprise Size

7.2.5.    By End-users

7.2.6.    By Country

7.3.  North America: Country Analysis

7.3.1.    United States Automated Machine Learning Solution Market Outlook

7.3.1.1.        Market Size & Forecast

7.3.1.1.1.           By Value 

7.3.1.2.        Market Share & Forecast

7.3.1.2.1.           By Offering

7.3.1.2.2.           By Deployment

7.3.1.2.3.           By Automation Type

7.3.1.2.4.           By Enterprise Size

7.3.1.2.5.           By End-users

7.3.2.    Canada Automated Machine Learning Solution Market Outlook

7.3.2.1.        Market Size & Forecast

7.3.2.1.1.           By Value 

7.3.2.2.        Market Share & Forecast

7.3.2.2.1.           By Offering

7.3.2.2.2.           By Deployment

7.3.2.2.3.           By Automation Type

7.3.2.2.4.           By Enterprise Size

7.3.2.2.5.           By End-users

7.3.3.    Mexico Automated Machine Learning Solution Market Outlook

7.3.3.1.        Market Size & Forecast

7.3.3.1.1.           By Value 

7.3.3.2.        Market Share & Forecast

7.3.3.2.1.           By Offering

7.3.3.2.2.           By Deployment

7.3.3.2.3.           By Automation Type

7.3.3.2.4.           By Enterprise Size

7.3.3.2.5.           By End-users

8.    Asia-Pacific Automated Machine Learning Solution Market Outlook

8.1.  Market Size & Forecast

8.1.1.    By Value

8.2.  Market Share & Forecast

8.2.1.    By Offering

8.2.2.    By Deployment

8.2.3.    By Automation Type

8.2.4.    By Enterprise Size

8.2.5.    By End-users

8.2.6.    By Country

8.3.  Asia-Pacific: Country Analysis

8.3.1.    China Automated Machine Learning Solution Market Outlook

8.3.1.1.        Market Size & Forecast

8.3.1.1.1.           By Value 

8.3.1.2.        Market Share & Forecast

8.3.1.2.1.           By Offering

8.3.1.2.2.           By Deployment

8.3.1.2.3.           By Automation Type

8.3.1.2.4.           By Enterprise Size

8.3.1.2.5.           By End-users

8.3.2.    India Automated Machine Learning Solution Market Outlook

8.3.2.1.        Market Size & Forecast

8.3.2.1.1.           By Value 

8.3.2.2.        Market Share & Forecast

8.3.2.2.1.           By Offering

8.3.2.2.2.           By Deployment

8.3.2.2.3.           By Automation Type

8.3.2.2.4.           By Enterprise Size

8.3.2.2.5.           By End-users

8.3.3.    Japan Automated Machine Learning Solution Market Outlook

8.3.3.1.        Market Size & Forecast

8.3.3.1.1.           By Value 

8.3.3.2.        Market Share & Forecast

8.3.3.2.1.           By Offering

8.3.3.2.2.           By Deployment

8.3.3.2.3.           By Automation Type

8.3.3.2.4.           By Enterprise Size

8.3.3.2.5.           By End-users

8.3.4.    South Korea Automated Machine Learning Solution Market Outlook

8.3.4.1.        Market Size & Forecast

8.3.4.1.1.           By Value 

8.3.4.2.        Market Share & Forecast

8.3.4.2.1.           By Offering

8.3.4.2.2.           By Deployment

8.3.4.2.3.           By Automation Type

8.3.4.2.4.           By Enterprise Size

8.3.4.2.5.           By End-users

8.3.5.    Australia Automated Machine Learning Solution Market Outlook

8.3.5.1.        Market Size & Forecast

8.3.5.1.1.           By Value 

8.3.5.2.        Market Share & Forecast

8.3.5.2.1.           By Offering

8.3.5.2.2.           By Deployment

8.3.5.2.3.           By Automation Type

8.3.5.2.4.           By Enterprise Size

8.3.5.2.5.           By End-users

8.3.6.    Singapore Automated Machine Learning Solution Market Outlook

8.3.6.1.        Market Size & Forecast

8.3.6.1.1.           By Value 

8.3.6.2.        Market Share & Forecast

8.3.6.2.1.           By Offering

8.3.6.2.2.           By Deployment

8.3.6.2.3.           By Automation Type

8.3.6.2.4.           By Enterprise Size

8.3.6.2.5.           By End-users

8.3.7.    Malaysia Automated Machine Learning Solution Market Outlook

8.3.7.1.        Market Size & Forecast

8.3.7.1.1.           By Value 

8.3.7.2.        Market Share & Forecast

8.3.7.2.1.           By Offering

8.3.7.2.2.           By Deployment

8.3.7.2.3.           By Automation Type

8.3.7.2.4.           By Enterprise Size

8.3.7.2.5.           By End-users

9.    Europe Automated Machine Learning Solution Market Outlook

9.1.  Market Size & Forecast

9.1.1.    By Value

9.2.  Market Share & Forecast

9.2.1.    By Offering

9.2.2.    By Deployment

9.2.3.    By Automation Type

9.2.4.    By Enterprise Size

9.2.5.    By End-users

9.2.6.    By Country

9.3.  Europe: Country Analysis

9.3.1.    Germany Automated Machine Learning Solution Market Outlook

9.3.1.1.        Market Size & Forecast

9.3.1.1.1.           By Value 

9.3.1.2.        Market Share & Forecast

9.3.1.2.1.           By Offering

9.3.1.2.2.           By Deployment

9.3.1.2.3.           By Automation Type

9.3.1.2.4.           By Enterprise Size

9.3.1.2.5.           By End-users

9.3.2.    United Kingdom Automated Machine Learning Solution Market Outlook

9.3.2.1.        Market Size & Forecast

9.3.2.1.1.           By Value 

9.3.2.2.        Market Share & Forecast

9.3.2.2.1.           By Offering

9.3.2.2.2.           By Deployment

9.3.2.2.3.           By Automation Type

9.3.2.2.4.           By Enterprise Size

9.3.2.2.5.           By End-users

9.3.3.    France Automated Machine Learning Solution Market Outlook

9.3.3.1.        Market Size & Forecast

9.3.3.1.1.           By Value 

9.3.3.2.        Market Share & Forecast

9.3.3.2.1.           By Offering

9.3.3.2.2.           By Deployment

9.3.3.2.3.           By Automation Type

9.3.3.2.4.           By Enterprise Size

9.3.3.2.5.           By End-users

9.3.4.    Russia Automated Machine Learning Solution Market Outlook

9.3.4.1.        Market Size & Forecast

9.3.4.1.1.           By Value 

9.3.4.2.        Market Share & Forecast

9.3.4.2.1.           By Offering

9.3.4.2.2.           By Deployment

9.3.4.2.3.           By Automation Type

9.3.4.2.4.           By Enterprise Size

9.3.4.2.5.           By End-users

9.3.5.    Spain Automated Machine Learning Solution Market Outlook

9.3.5.1.        Market Size & Forecast

9.3.5.1.1.           By Value 

9.3.5.2.        Market Share & Forecast

9.3.5.2.1.           By Offering

9.3.5.2.2.           By Deployment

9.3.5.2.3.           By Automation Type

9.3.5.2.4.           By Enterprise Size

9.3.5.2.5.           By End-users

9.3.6.    Belgium Automated Machine Learning Solution Market Outlook

9.3.6.1.        Market Size & Forecast

9.3.6.1.1.           By Value 

9.3.6.2.        Market Share & Forecast

9.3.6.2.1.           By Offering

9.3.6.2.2.           By Deployment

9.3.6.2.3.           By Automation Type

9.3.6.2.4.           By Enterprise Size

9.3.6.2.5.           By End-users

9.3.7.    Italy Automated Machine Learning Solution Market Outlook

9.3.7.1.        Market Size & Forecast

9.3.7.1.1.           By Value 

9.3.7.2.        Market Share & Forecast

9.3.7.2.1.           By Offering

9.3.7.2.2.           By Deployment

9.3.7.2.3.           By Automation Type

9.3.7.2.4.           By Enterprise Size

9.3.7.2.5.           By End-users

10. South America Automated Machine Learning Solution Market Outlook

10.1.             Market Size & Forecast

10.1.1. By Value

10.2.             Market Share & Forecast

10.2.1. By Offering

10.2.2. By Deployment

10.2.3. By Automation Type

10.2.4. By Enterprise Size

10.2.5. By End-users

10.2.6. By Country

10.3.             South America: Country Analysis

10.3.1. Brazil Automated Machine Learning Solution Market Outlook

10.3.1.1.     Market Size & Forecast

10.3.1.1.1.         By Value 

10.3.1.2.     Market Share & Forecast

10.3.1.2.1.         By Offering

10.3.1.2.2.         By Deployment

10.3.1.2.3.         By Automation Type

10.3.1.2.4.         By Enterprise Size

10.3.1.2.5.         By End-users

10.3.2. Argentina Automated Machine Learning Solution Market Outlook

10.3.2.1.     Market Size & Forecast

10.3.2.1.1.         By Value 

10.3.2.2.     Market Share & Forecast

10.3.2.2.1.         By Offering

10.3.2.2.2.         By Deployment

10.3.2.2.3.         By Automation Type

10.3.2.2.4.         By Enterprise Size

10.3.2.2.5.         By End-users

10.3.3. Colombia Automated Machine Learning Solution Market Outlook

10.3.3.1.     Market Size & Forecast

10.3.3.1.1.         By Value 

10.3.3.2.     Market Share & Forecast

10.3.3.2.1.         By Offering

10.3.3.2.2.         By Deployment

10.3.3.2.3.         By Automation Type

10.3.3.2.4.         By Enterprise Size

10.3.3.2.5.         By End-users

10.3.4. Peru Automated Machine Learning Solution Market Outlook

10.3.4.1.     Market Size & Forecast

10.3.4.1.1.         By Value 

10.3.4.2.     Market Share & Forecast

10.3.4.2.1.         By Offering

10.3.4.2.2.         By Deployment

10.3.4.2.3.         By Automation Type

10.3.4.2.4.         By Enterprise Size

10.3.4.2.5.         By End-users

10.3.5. Chile Automated Machine Learning Solution Market Outlook

10.3.5.1.     Market Size & Forecast

10.3.5.1.1.         By Value 

10.3.5.2.     Market Share & Forecast

10.3.5.2.1.         By Offering

10.3.5.2.2.         By Deployment

10.3.5.2.3.         By Automation Type

10.3.5.2.4.         By Enterprise Size

10.3.5.2.5.         By End-users

11. Middle East & Africa Automated Machine Learning Solution Market Outlook

11.1.             Market Size & Forecast

11.1.1. By Value

11.2.             Market Share & Forecast

11.2.1. By Offering

11.2.2. By Deployment

11.2.3. By Automation Type

11.2.4. By Enterprise Size

11.2.5. By End-users

11.2.6. By Country

11.3.             Middle East & Africa: Country Analysis

11.3.1. Saudi Arabia Automated Machine Learning Solution Market Outlook

11.3.1.1.     Market Size & Forecast

11.3.1.1.1.         By Value 

11.3.1.2.     Market Share & Forecast

11.3.1.2.1.         By Offering

11.3.1.2.2.         By Deployment

11.3.1.2.3.         By Automation Type

11.3.1.2.4.         By Enterprise Size

11.3.1.2.5.         By End-users

11.3.2. South Africa Automated Machine Learning Solution Market Outlook

11.3.2.1.     Market Size & Forecast

11.3.2.1.1.         By Value 

11.3.2.2.     Market Share & Forecast

11.3.2.2.1.         By Offering

11.3.2.2.2.         By Deployment

11.3.2.2.3.         By Automation Type

11.3.2.2.4.         By Enterprise Size

11.3.2.2.5.         By End-users

11.3.3. UAE Automated Machine Learning Solution Market Outlook

11.3.3.1.     Market Size & Forecast

11.3.3.1.1.         By Value 

11.3.3.2.     Market Share & Forecast

11.3.3.2.1.         By Offering

11.3.3.2.2.         By Deployment

11.3.3.2.3.         By Automation Type

11.3.3.2.4.         By Enterprise Size

11.3.3.2.5.         By End-users

11.3.4. Israel Automated Machine Learning Solution Market Outlook

11.3.4.1.     Market Size & Forecast

11.3.4.1.1.         By Value 

11.3.4.2.     Market Share & Forecast

11.3.4.2.1.         By Offering

11.3.4.2.2.         By Deployment

11.3.4.2.3.         By Automation Type

11.3.4.2.4.         By Enterprise Size

11.3.4.2.5.         By End-users

11.3.5. Turkey Automated Machine Learning Solution Market Outlook

11.3.5.1.     Market Size & Forecast

11.3.5.1.1.         By Value 

11.3.5.2.     Market Share & Forecast

11.3.5.2.1.         By Offering

11.3.5.2.2.         By Deployment

11.3.5.2.3.         By Automation Type

11.3.5.2.4.         By Enterprise Size

11.3.5.2.5.         By End-users

12. Market Dynamics

12.1. Drivers

12.2. Challenges

13. Market Trends & Developments

14. Company Profiles

14.1.             Datarobot Inc.

14.1.1. Business Overview

14.1.2. Key Revenue and Financials

14.1.3. Recent Developments

14.1.4. Key Personnel

14.1.5. Key Product/Services

14.2.             Amazon Web Services Inc.

14.2.1. Business Overview

14.2.2. Key Revenue and Financials

14.2.3. Recent Developments

14.2.4. Key Personnel

14.2.5. Key Product/Services

14.3.             dotData Inc.

14.3.1. Business Overview

14.3.2. Key Revenue and Financials

14.3.3. Recent Developments

14.3.4. Key Personnel

14.3.5. Key Product/Services

14.4.             IBM Corporation

14.4.1. Business Overview

14.4.2. Key Revenue and Financials

14.4.3. Recent Developments

14.4.4. Key Personnel

14.4.5. Key Product/Services

14.5.             Dataiku

14.5.1. Business Overview

14.5.2. Key Revenue and Financials

14.5.3. Recent Developments

14.5.4. Key Personnel

14.5.5. Key Product/Services

14.6.             EdgeVerve Systems Limited

14.6.1. Business Overview

14.6.2. Key Revenue and Financials

14.6.3. Recent Developments

14.6.4. Key Personnel

14.6.5. Key Product/Services

14.7.             Big Squid Inc.

14.7.1. Business Overview

14.7.2. Key Revenue and Financials

14.7.3. Recent Developments

14.7.4. Key Personnel

14.7.5. Key Product/Services

14.8.             SAS Institute Inc.

14.8.1. Business Overview

14.8.2. Key Revenue and Financials

14.8.3. Recent Developments

14.8.4. Key Personnel

14.8.5. Key Product/Services

14.9.             Microsoft Corporation

14.9.1. Business Overview

14.9.2. Key Revenue and Financials

14.9.3. Recent Developments

14.9.4. Key Personnel

14.9.5. Key Product/Services

14.10.          Determined.ai Inc

14.10.1.  Business Overview

14.10.2.  Key Revenue and Financials

14.10.3.  Recent Developments

14.10.4.  Key Personnel

14.10.5.  Key Product/Services

15. Strategic Recommendations

16. About Us & Disclaimer

Figures and Tables

Frequently asked questions

Frequently asked questions

Datarobot Inc., Amazon Web Services Inc., dotData Inc., IBM Corporation, Dataiku, EdgeVerve Systems Limited, Big Squid Inc., SAS Institute Inc., Microsoft Corporation, and Determined.ai Inc.

Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems.

Asia-Pacific is the fastest-growing region in the automated machine learning solution market due to growing IT sector and government initiative.

Increased need for effective fraud detection tools and rising demand for individualised product suggestions are the major drivers of the global automated machine learing solutions.

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