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Anomaly Detection Market Size, Share & Industry Trends Analysis Report By Deployment, By Technology, By Component (Solution (Network Behavior, and User Behavior), and Services), By End-Use, By Regional Outlook and Forecast, 2023 - 2030

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    Report

  • 332 Pages
  • July 2023
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5869061
The Global Anomaly Detection Market size is expected to reach $13.4 billion by 2030, rising at a market growth of 15.9% CAGR during the forecast period.

The digital economy has swiftly grown throughout the region of Asia Pacific as a result of a strong increase in e-commerce activity, online transactions, and digital services. Consequently, the Asia Pacific region will acquire approximately 1/4thshare in the market by 2030. The need for anomaly detection has grown due to this expansion to identify and handle potential fraud, security flaws, and other anomalies in these digital transactions. The regional financial services sector is expanding rapidly because of growing banking services, fintech advancements, and a rise in digital payments. Anomaly detection is crucial for Anti-Money Laundering (AML) initiatives, fraud prevention, and legal compliance in this sector.



The major strategies followed by the market participants are Partnerships as the key developmental strategy to keep pace with the changing demands of end users. For instance, In June, 20223, Amazon Web Services Inc. expanded its partnership with Lacework Inc. to enhance security alerts and provide its clients an improved anomaly detection linked with Amazon Guard Duty findings. Additionally, In December, 2021, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company formed a collaboration with Pfizer, to develop a prototype solution for detecting abnormal data points in its drug product continuous clinical manufacturing platform for solid oral-dose medicines.

The Cardinal Matrix - Market Competition Analysis


Based on the Analysis presented in the The Cardinal Matrix; Microsoft Corporation is the forerunner in the Market. Companies such as Cisco Systems, Inc., Broadcom, Inc., Dell Technologies, Inc. are some of the key innovators in the Market. In March, 2022, Cisco Systems, Inc teamed up with NetApp to provide the joint customers of the two companies with automation, hybrid cloud operations, and visibility solutions.



Market Growth Factors

Increasing volume of data and connected devices

Anomaly detection is becoming increasingly necessary as the number of linked devices is increasing in banking, IT, healthcare, finance, manufacturing, and government & defense. The widespread use of IoT solutions that actively participate in various technological advancements significantly impacts the IoT industry. The market has seen an upsurge due to the increasing use of cloud-based IoT devices, which has increased competition to provide the best solutions to various end-use industries. Moreover, one of the main causes of the IoT industry's enormous development is considerable government attempts to digitalize businesses and sectors.

Artificial intelligence (AI) and machine learning (ML) advancements

The ability to detect anomalies has substantially increased because of developments in AI and machine learning techniques. Artificial intelligence (AI) may aid in many ways, including automation, real-time analysis, scrupulosity, accuracy, and self-learning, when human resources are insufficient to handle the adaptable framework of cloud infrastructure, microservices, and containers. One of the greatest benefits of AI systems as well as ML-based solutions, is their ability to learn as they go along and provide better and more accurate results with each iteration. Hence, AI-powered anomaly detection tools can evaluate complicated patterns, adapt to shifting surroundings, and accurately pinpoint anomalies, spurring market expansion.

Market Restraining Factors

Issues with false alarms and system implementation

Anomaly detection systems can be challenging to build and tune to identify true anomalies while avoiding false positives (or false alarms). High rates of false positives could reduce user confidence in the system's accuracy and lead to warning fatigue, which could prevent product uptake. False positive rates that are too high can cause alert fatigue and a lack of faith in the system, whereas false negative rates that are too low can leave serious anomalies unnoticed. For the market to expand, anomaly detection algorithms' accuracy must be improved. Integrating anomaly detection tools with current workflows and systems can be difficult and time-consuming. Implementing anomaly detection technology may be slowed down by organizations facing compatibility problems with legacy systems. Thus, these factors may hamper the market's growth in the coming years.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

Deployment Outlook

Based on deployment, the market is segmented into cloud and on-premise. The cloud segment acquired a substantial revenue share in the market in 2022. Cloud-based anomaly detection systems are unsurpassed in their adaptability and scalability. Organizations may easily scale up or down anomaly detection capabilities in accordance with their needs because of cloud infrastructure. Because data processing and volume requirements fluctuate over time, organizations don't need to spend much money on infrastructure or plan for capacity with cloud infrastructure.

Technology Outlook

On the basis of technology, the market is classified into machine learning & artificial intelligence, big data analytics, and business intelligence & data mining. The big data analytics segment recorded the largest revenue share in the market in 2022. As connected devices and digital technology advance, businesses produce and collect large amounts of data from multiple sources. Manually finding irregularities can be challenging because this data is available in both unstructured, structured, and semi-structured, formats.



Component Outlook

Based on component, the market is bifurcated into solution and services. The services segment procured a considerable growth rate in the market in 2022. Cloud-based security service solutions commonly incorporate anomaly detection services. With the help of these services, enterprises can easily and affordably set up as well as maintain anomaly detection operations.

Solution Outlook

On the basis of the solution, the market is classified into network behavior and user behavior. The network behavior segment acquired the largest revenue share in the market in 2022. Network behavior analysis is required for the operation of network behavior anomaly detection. Machine learning (ML) and artificial intelligence (AI) are used in network behavior anomaly detection to identify hidden hazards in areas of network infrastructure where other security technologies cannot access them and to alert network personnel.

End-Use Outlook

By end-use, the market is characterized into BFSI, retail, IT & telecom, healthcare, manufacturing, government & defense, and others. The BFSI segment garnered the maximum revenue share in the market in 2022. Risk management is crucial to the BFSI industry. Anomaly detection makes it possible to identify potential risks, including market risk, operational risk, credit risk, and fraud risk. By identifying anomalies in financial transactions, customer behavior, or market patterns, organizations can assess and minimize risks, make intelligent decisions, and prevent financial losses.

Regional Outlook

Region wise, the market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The North America segment recorded the highest revenue share in the market in 2022. The continent of North America is subject to an unstable environment that is changing quickly, especially regarding cybersecurity. The proliferation of digital technology, along with the development of big data, has also led to huge data production and collection by companies. Anomaly detection is essential for spotting fraudulent activities in the insurance, e-commerce, financial, and healthcare sectors. By monitoring patterns and anomalies in transactional data or user behavior, businesses can proactively identify and lower the risk of fraud.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., Broadcom, Inc., Cisco Systems, Inc., Dell Technologies, Inc., Dynatrace, Inc., Happiest Minds Technologies Limited, Hewlett Packard Enterprise Company, IBM Corporation, Microsoft Corporation and SAS Institute, Inc.

Strategies Deployed in the Market

Partnerships, Collaborations, and Agreements:

  • Jun-2023: Amazon Web Services Inc. expanded its partnership with Lacework Inc., a cloud security company. Lacework would integrate its services with AWS Security Hub to enhance security alerts and provide its clients an improved anomaly detection linked with Amazon GuardDuty findings.
  • May-2023: Amazon Web Services joined hands with Elastic, distributed, free, and open search and analytics engine for all types of data. The collaboration aims at offering a seamless user experience for Elastic Cloud on AWS. Moreover, it would support its client's global cloud adoption journey and help boost their digital transformation.
  • Nov-2022: Happiest Minds Technologies Limited formed a collaboration with ServiceNow, a software company that provides a cloud-based platform for automating IT management workflows. With this collaboration, the company aims to enhance its IT service offerings globally.
  • May-2022: IBM Corporation signed an agreement with Amazon Web Services (AWS), a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments. This agreement would deliver IBM's clients easy and rapid access to IBM Software that covers Data and AI, Security, Sustainability, and Automation abilities.
  • Mar-2022: Cisco Systems, Inc teamed up with NetApp, a data management solutions provider. The partnership would provide the joint customers of the two companies with automation, hybrid cloud operations, and visibility solutions.
  • Dec-2021: Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company formed a collaboration with Pfizer, an American multinational pharmaceutical and biotechnology corporation. The company would apply its analytics, machine learning, computing, storage, security, and cloud data warehousing capabilities to Pfizer laboratory, clinical manufacturing, and clinical supply chain efforts. Furthermore, the company aimed to develop a prototype solution for detecting abnormal data points in its drug product continuous clinical manufacturing platform for solid oral-dose medicines.
  • Aug-2021: IBM teamed up with Black & Veatch, an engineering, procurement, consulting, and construction company. The collaboration integrates Black & Veatch Asset Management Services (AMS) and digital analytics with IBM Maximo Application Suite to enhance the performance of assets and extend their lifespans.

»Product Launches and Product Expansions:

  • Mar-2021: Amazon Web Services revealed Amazon Lookout for Metrics, an anomaly detection service, to monitor the health of its client's businesses. The new service aims at opening machine learning technology to more manufacturing plants by removing barriers involved in developing, training, deploying, monitoring, and fine-tuning computer vision models.

Acquisition and Mergers:

  • Mar-2023: Cisco Systems, Inc completed the acquisition of Lightspin Technologies Ltd., a security software provider based in Israel. The acquisition would enhance Cisco's ability to deliver secure solutions for cloud environments to their customers.
  • Jul-2022: IBM took over Databand.ai, a leading provider of data observability software. This acquisition aimed to provide IBM with the most comprehensive set of observability offerings for IT across applications, data, and machine learning and would continue to provide IBM's customers and partners with the technology they require to provide trustworthy data and AI at scale.
  • Mar-2022: Microsoft took over Nuance Communications, a leader in conversational AI and ambient intelligence industries. This acquisition aimed to bring together Nuance’s best-in-class conversational AI and ambient intelligence with Microsoft’s secure as well as trusted industry cloud offerings. Also, this acquisition would help providers offer more affordable, effective, and accessible healthcare, and help businesses in every industry create more personalized and meaningful customer experiences.

Scope of the Study

By Deployment

  • On-premise
  • Cloud

By Technology

  • Big Data Analytics
  • Business Intelligence & Data Mining
  • Machine Learning & Artificial Intelligence

By Component

  • Solution
    • Network Behavior
    • User Behavior
  • Services

By End-Use

  • BFSI
  • Government & Defense
  • IT & Telecom
  • Healthcare
  • Manufacturing
  • Retail
  • Others

By Geography

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • Amazon Web Services, Inc.
  • Broadcom, Inc.
  • Cisco Systems, Inc.
  • Dell Technologies, Inc.
  • Dynatrace, Inc.
  • Happiest Minds Technologies Limited
  • Hewlett Packard Enterprise Company
  • IBM Corporation
  • Microsoft Corporation
  • SAS Institute, Inc.

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Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Anomaly Detection Market, by Deployment
1.4.2 Global Anomaly Detection Market, by Technology
1.4.3 Global Anomaly Detection Market, by Component
1.4.4 Global Anomaly Detection Market, by End-Use
1.4.5 Global Anomaly Detection Market, by Geography
1.5 Methodology for the research
Chapter 2. Market At a Glance
2.1 Key Highlight
Chapter 3. Market Overview
3.1 Introduction
3.1.1 Overview
3.1.1.1 Market Composition and Scenario
3.2 Key Factors Impacting the Market
3.2.1 Market Drivers
3.2.2 Market Restraints
Chapter 4. Competition Analysis - Global
4.1 KBV Cardinal Matrix
4.2 Recent Industry Wide Strategic Developments
4.2.1 Partnerships, Collaborations and Agreements
4.2.2 Product Launches and Product Expansions
4.2.3 Acquisition and Mergers
4.3 Market Share Analysis, 2021
4.4 Top Winning Strategies
4.4.1 Key Leading Strategies: Percentage Distribution (2019-2023)
4.4.2 Key Strategic Move: (Partnerships, Collaborations and Agreements: 2021, Aug - 2023, Jun) Leading Players
4.5 Porter Five Forces Analysis
Chapter 5. Global Anomaly Detection Market by Deployment
5.1 Global On-premise Market by Region
5.2 Global Cloud Market by Region
Chapter 6. Global Anomaly Detection Market by Technology
6.1 Global Big Data Analytics Market by Region
6.2 Global Business Intelligence & Data Mining Market by Region
6.3 Global Machine Learning & Artificial Intelligence Market by Region
Chapter 7. Global Anomaly Detection Market by Component
7.1 Global Solution Market by Region
7.2 Global Anomaly Detection Market by Solution Type
7.2.1 Global Network Behavior Market by Region
7.2.2 Global User Behavior Market by Region
7.3 Global Services Market by Region
Chapter 8. Global Anomaly Detection Market by End-use
8.1 Global BFSI Market by Region
8.2 Global Government & Defense Market by Region
8.3 Global IT & Telecom Market by Region
8.4 Global Healthcare Market by Region
8.5 Global Manufacturing Market by Region
8.6 Global Retail Market by Region
8.7 Global Others Market by Region
Chapter 9. Global Anomaly Detection Market by Region
9.1 North America Anomaly Detection Market
9.1.1 North America Anomaly Detection Market by Deployment
9.1.1.1 North America On-premise Market by Country
9.1.1.2 North America Cloud Market by Country
9.1.2 North America Anomaly Detection Market by Technology
9.1.2.1 North America Big Data Analytics Market by Country
9.1.2.2 North America Business Intelligence & Data Mining Market by Country
9.1.2.3 North America Machine Learning & Artificial Intelligence Market by Country
9.1.3 North America Anomaly Detection Market by Component
9.1.3.1 North America Solution Market by Country
9.1.3.2 North America Anomaly Detection Market by Solution Type
9.1.3.2.1 North America Network Behavior Market by Country
9.1.3.2.2 North America User Behavior Market by Country
9.1.3.3 North America Services Market by Country
9.1.4 North America Anomaly Detection Market by End-use
9.1.4.1 North America BFSI Market by Country
9.1.4.2 North America Government & Defense Market by Country
9.1.4.3 North America IT & Telecom Market by Country
9.1.4.4 North America Healthcare Market by Country
9.1.4.5 North America Manufacturing Market by Country
9.1.4.6 North America Retail Market by Country
9.1.4.7 North America Others Market by Country
9.1.5 North America Anomaly Detection Market by Country
9.1.5.1 US Anomaly Detection Market
9.1.5.1.1 US Anomaly Detection Market by Deployment
9.1.5.1.2 US Anomaly Detection Market by Technology
9.1.5.1.3 US Anomaly Detection Market by Component
9.1.5.1.4 US Anomaly Detection Market by End-use
9.1.5.2 Canada Anomaly Detection Market
9.1.5.2.1 Canada Anomaly Detection Market by Deployment
9.1.5.2.2 Canada Anomaly Detection Market by Technology
9.1.5.2.3 Canada Anomaly Detection Market by Component
9.1.5.2.4 Canada Anomaly Detection Market by End-use
9.1.5.3 Mexico Anomaly Detection Market
9.1.5.3.1 Mexico Anomaly Detection Market by Deployment
9.1.5.3.2 Mexico Anomaly Detection Market by Technology
9.1.5.3.3 Mexico Anomaly Detection Market by Component
9.1.5.3.4 Mexico Anomaly Detection Market by End-use
9.1.5.4 Rest of North America Anomaly Detection Market
9.1.5.4.1 Rest of North America Anomaly Detection Market by Deployment
9.1.5.4.2 Rest of North America Anomaly Detection Market by Technology
9.1.5.4.3 Rest of North America Anomaly Detection Market by Component
9.1.5.4.4 Rest of North America Anomaly Detection Market by End-use
9.2 Europe Anomaly Detection Market
9.2.1 Europe Anomaly Detection Market by Deployment
9.2.1.1 Europe On-premise Market by Country
9.2.1.2 Europe Cloud Market by Country
9.2.2 Europe Anomaly Detection Market by Technology
9.2.2.1 Europe Big Data Analytics Market by Country
9.2.2.2 Europe Business Intelligence & Data Mining Market by Country
9.2.2.3 Europe Machine Learning & Artificial Intelligence Market by Country
9.2.3 Europe Anomaly Detection Market by Component
9.2.3.1 Europe Solution Market by Country
9.2.3.2 Europe Anomaly Detection Market by Solution Type
9.2.3.2.1 Europe Network Behavior Market by Country
9.2.3.2.2 Europe User Behavior Market by Country
9.2.3.3 Europe Services Market by Country
9.2.4 Europe Anomaly Detection Market by End-use
9.2.4.1 Europe BFSI Market by Country
9.2.4.2 Europe Government & Defense Market by Country
9.2.4.3 Europe IT & Telecom Market by Country
9.2.4.4 Europe Healthcare Market by Country
9.2.4.5 Europe Manufacturing Market by Country
9.2.4.6 Europe Retail Market by Country
9.2.4.7 Europe Others Market by Country
9.2.5 Europe Anomaly Detection Market by Country
9.2.5.1 Germany Anomaly Detection Market
9.2.5.1.1 Germany Anomaly Detection Market by Deployment
9.2.5.1.2 Germany Anomaly Detection Market by Technology
9.2.5.1.3 Germany Anomaly Detection Market by Component
9.2.5.1.4 Germany Anomaly Detection Market by End-use
9.2.5.2 UK Anomaly Detection Market
9.2.5.2.1 UK Anomaly Detection Market by Deployment
9.2.5.2.2 UK Anomaly Detection Market by Technology
9.2.5.2.3 UK Anomaly Detection Market by Component
9.2.5.2.4 UK Anomaly Detection Market by End-use
9.2.5.3 France Anomaly Detection Market
9.2.5.3.1 France Anomaly Detection Market by Deployment
9.2.5.3.2 France Anomaly Detection Market by Technology
9.2.5.3.3 France Anomaly Detection Market by Component
9.2.5.3.4 France Anomaly Detection Market by End-use
9.2.5.4 Russia Anomaly Detection Market
9.2.5.4.1 Russia Anomaly Detection Market by Deployment
9.2.5.4.2 Russia Anomaly Detection Market by Technology
9.2.5.4.3 Russia Anomaly Detection Market by Component
9.2.5.4.4 Russia Anomaly Detection Market by End-use
9.2.5.5 Spain Anomaly Detection Market
9.2.5.5.1 Spain Anomaly Detection Market by Deployment
9.2.5.5.2 Spain Anomaly Detection Market by Technology
9.2.5.5.3 Spain Anomaly Detection Market by Component
9.2.5.5.4 Spain Anomaly Detection Market by End-use
9.2.5.6 Italy Anomaly Detection Market
9.2.5.6.1 Italy Anomaly Detection Market by Deployment
9.2.5.6.2 Italy Anomaly Detection Market by Technology
9.2.5.6.3 Italy Anomaly Detection Market by Component
9.2.5.6.4 Italy Anomaly Detection Market by End-use
9.2.5.7 Rest of Europe Anomaly Detection Market
9.2.5.7.1 Rest of Europe Anomaly Detection Market by Deployment
9.2.5.7.2 Rest of Europe Anomaly Detection Market by Technology
9.2.5.7.3 Rest of Europe Anomaly Detection Market by Component
9.2.5.7.4 Rest of Europe Anomaly Detection Market by End-use
9.3 Asia Pacific Anomaly Detection Market
9.3.1 Asia Pacific Anomaly Detection Market by Deployment
9.3.1.1 Asia Pacific On-premise Market by Country
9.3.1.2 Asia Pacific Cloud Market by Country
9.3.2 Asia Pacific Anomaly Detection Market by Technology
9.3.2.1 Asia Pacific Big Data Analytics Market by Country
9.3.2.2 Asia Pacific Business Intelligence & Data Mining Market by Country
9.3.2.3 Asia Pacific Machine Learning & Artificial Intelligence Market by Country
9.3.3 Asia Pacific Anomaly Detection Market by Component
9.3.3.1 Asia Pacific Solution Market by Country
9.3.3.2 Asia Pacific Anomaly Detection Market by Solution Type
9.3.3.2.1 Asia Pacific Network Behavior Market by Country
9.3.3.2.2 Asia Pacific User Behavior Market by Country
9.3.3.3 Asia Pacific Services Market by Country
9.3.4 Asia Pacific Anomaly Detection Market by End-use
9.3.4.1 Asia Pacific BFSI Market by Country
9.3.4.2 Asia Pacific Government & Defense Market by Country
9.3.4.3 Asia Pacific IT & Telecom Market by Country
9.3.4.4 Asia Pacific Healthcare Market by Country
9.3.4.5 Asia Pacific Manufacturing Market by Country
9.3.4.6 Asia Pacific Retail Market by Country
9.3.4.7 Asia Pacific Others Market by Country
9.3.5 Asia Pacific Anomaly Detection Market by Country
9.3.5.1 China Anomaly Detection Market
9.3.5.1.1 China Anomaly Detection Market by Deployment
9.3.5.1.2 China Anomaly Detection Market by Technology
9.3.5.1.3 China Anomaly Detection Market by Component
9.3.5.1.4 China Anomaly Detection Market by End-use
9.3.5.2 Japan Anomaly Detection Market
9.3.5.2.1 Japan Anomaly Detection Market by Deployment
9.3.5.2.2 Japan Anomaly Detection Market by Technology
9.3.5.2.3 Japan Anomaly Detection Market by Component
9.3.5.2.4 Japan Anomaly Detection Market by End-use
9.3.5.3 India Anomaly Detection Market
9.3.5.3.1 India Anomaly Detection Market by Deployment
9.3.5.3.2 India Anomaly Detection Market by Technology
9.3.5.3.3 India Anomaly Detection Market by Component
9.3.5.3.4 India Anomaly Detection Market by End-use
9.3.5.4 South Korea Anomaly Detection Market
9.3.5.4.1 South Korea Anomaly Detection Market by Deployment
9.3.5.4.2 South Korea Anomaly Detection Market by Technology
9.3.5.4.3 South Korea Anomaly Detection Market by Component
9.3.5.4.4 South Korea Anomaly Detection Market by End-use
9.3.5.5 Singapore Anomaly Detection Market
9.3.5.5.1 Singapore Anomaly Detection Market by Deployment
9.3.5.5.2 Singapore Anomaly Detection Market by Technology
9.3.5.5.3 Singapore Anomaly Detection Market by Component
9.3.5.5.4 Singapore Anomaly Detection Market by End-use
9.3.5.6 Malaysia Anomaly Detection Market
9.3.5.6.1 Malaysia Anomaly Detection Market by Deployment
9.3.5.6.2 Malaysia Anomaly Detection Market by Technology
9.3.5.6.3 Malaysia Anomaly Detection Market by Component
9.3.5.6.4 Malaysia Anomaly Detection Market by End-use
9.3.5.7 Rest of Asia Pacific Anomaly Detection Market
9.3.5.7.1 Rest of Asia Pacific Anomaly Detection Market by Deployment
9.3.5.7.2 Rest of Asia Pacific Anomaly Detection Market by Technology
9.3.5.7.3 Rest of Asia Pacific Anomaly Detection Market by Component
9.3.5.7.4 Rest of Asia Pacific Anomaly Detection Market by End-use
9.4 LAMEA Anomaly Detection Market
9.4.1 LAMEA Anomaly Detection Market by Deployment
9.4.1.1 LAMEA On-premise Market by Country
9.4.1.2 LAMEA Cloud Market by Country
9.4.2 LAMEA Anomaly Detection Market by Technology
9.4.2.1 LAMEA Big Data Analytics Market by Country
9.4.2.2 LAMEA Business Intelligence & Data Mining Market by Country
9.4.2.3 LAMEA Machine Learning & Artificial Intelligence Market by Country
9.4.3 LAMEA Anomaly Detection Market by Component
9.4.3.1 LAMEA Solution Market by Country
9.4.3.2 LAMEA Anomaly Detection Market by Solution Type
9.4.3.2.1 LAMEA Network Behavior Market by Country
9.4.3.2.2 LAMEA User Behavior Market by Country
9.4.3.3 LAMEA Services Market by Country
9.4.4 LAMEA Anomaly Detection Market by End-use
9.4.4.1 LAMEA BFSI Market by Country
9.4.4.2 LAMEA Government & Defense Market by Country
9.4.4.3 LAMEA IT & Telecom Market by Country
9.4.4.4 LAMEA Healthcare Market by Country
9.4.4.5 LAMEA Manufacturing Market by Country
9.4.4.6 LAMEA Retail Market by Country
9.4.4.7 LAMEA Others Market by Country
9.4.5 LAMEA Anomaly Detection Market by Country
9.4.5.1 Brazil Anomaly Detection Market
9.4.5.1.1 Brazil Anomaly Detection Market by Deployment
9.4.5.1.2 Brazil Anomaly Detection Market by Technology
9.4.5.1.3 Brazil Anomaly Detection Market by Component
9.4.5.1.4 Brazil Anomaly Detection Market by End-use
9.4.5.2 Argentina Anomaly Detection Market
9.4.5.2.1 Argentina Anomaly Detection Market by Deployment
9.4.5.2.2 Argentina Anomaly Detection Market by Technology
9.4.5.2.3 Argentina Anomaly Detection Market by Component
9.4.5.2.4 Argentina Anomaly Detection Market by End-use
9.4.5.3 UAE Anomaly Detection Market
9.4.5.3.1 UAE Anomaly Detection Market by Deployment
9.4.5.3.2 UAE Anomaly Detection Market by Technology
9.4.5.3.3 UAE Anomaly Detection Market by Component
9.4.5.3.4 UAE Anomaly Detection Market by End-use
9.4.5.4 Saudi Arabia Anomaly Detection Market
9.4.5.4.1 Saudi Arabia Anomaly Detection Market by Deployment
9.4.5.4.2 Saudi Arabia Anomaly Detection Market by Technology
9.4.5.4.3 Saudi Arabia Anomaly Detection Market by Component
9.4.5.4.4 Saudi Arabia Anomaly Detection Market by End-use
9.4.5.5 South Africa Anomaly Detection Market
9.4.5.5.1 South Africa Anomaly Detection Market by Deployment
9.4.5.5.2 South Africa Anomaly Detection Market by Technology
9.4.5.5.3 South Africa Anomaly Detection Market by Component
9.4.5.5.4 South Africa Anomaly Detection Market by End-use
9.4.5.6 Nigeria Anomaly Detection Market
9.4.5.6.1 Nigeria Anomaly Detection Market by Deployment
9.4.5.6.2 Nigeria Anomaly Detection Market by Technology
9.4.5.6.3 Nigeria Anomaly Detection Market by Component
9.4.5.6.4 Nigeria Anomaly Detection Market by End-use
9.4.5.7 Rest of LAMEA Anomaly Detection Market
9.4.5.7.1 Rest of LAMEA Anomaly Detection Market by Deployment
9.4.5.7.2 Rest of LAMEA Anomaly Detection Market by Technology
9.4.5.7.3 Rest of LAMEA Anomaly Detection Market by Component
9.4.5.7.4 Rest of LAMEA Anomaly Detection Market by End-use
Chapter 10. Company Profiles
10.1 Amazon Web Services, Inc. (Amazon.com, Inc.)
10.1.1 Company Overview
10.1.2 Financial Analysis
10.1.3 Segmental Analysis
10.1.4 Recent strategies and developments:
10.1.4.1 Partnerships, Collaborations, and Agreements:
10.1.4.2 Product Launches and Product Expansions:
10.1.5 SWOT Analysis
10.2 Broadcom, Inc.
10.2.1 Company Overview
10.2.2 Financial Analysis
10.2.3 Segmental and Regional Analysis
10.2.4 Research & Development Expense
10.2.5 Recent strategies and developments:
10.2.5.1 Acquisition and Mergers:
10.2.6 SWOT Analysis
10.3 Cisco Systems, Inc.
10.3.1 Company Overview
10.3.2 Financial Analysis
10.3.3 Regional Analysis
10.3.4 Research & Development Expense
10.3.5 Recent strategies and developments:
10.3.5.1 Partnerships, Collaborations, and Agreements:
10.3.5.2 Acquisition and Mergers:
10.3.6 SWOT Analysis
10.4 Dell Technologies, Inc.
10.4.1 Company Overview
10.4.2 Financial Analysis
10.4.3 Segmental and Regional Analysis
10.4.4 Research & Development Expense
10.4.5 SWOT Analysis:
10.5 Dynatrace, Inc.
10.5.1 Company Overview
10.5.2 SWOT Analysis:
10.6 Happiest Minds Technologies Limited
10.6.1 Company Overview
10.6.2 Recent strategies and developments:
10.6.2.1 Partnerships, Collaborations, and Agreements:
10.6.3 SWOT Analysis:
10.7 Hewlett Packard Enterprise Company
10.7.1 Company Overview
10.7.2 Financial Analysis
10.7.3 Segmental and Regional Analysis
10.7.4 Research & Development Expense
10.7.5 SWOT Analysis
10.8 IBM Corporation
10.8.1 Company Overview
10.8.2 Financial Analysis
10.8.3 Regional & Segmental Analysis
10.8.4 Research & Development Expenses
10.8.5 Recent strategies and developments:
10.8.5.1 Partnerships, Collaborations, and Agreements:
10.8.5.2 Product Launches and Product Expansions:
10.8.5.3 Acquisition and Mergers:
10.8.6 SWOT Analysis
10.9 Microsoft Corporation
10.9.1 Company Overview
10.9.2 Financial Analysis
10.9.3 Segmental and Regional Analysis
10.9.4 Research & Development Expenses
10.9.5 Recent strategies and developments:
10.9.5.1 Acquisition and Mergers:
10.9.6 SWOT Analysis
10.10. SAS Institute, Inc.
10.10.1 Company Overview
10.10.2 SWOT Analysis
Chapter 11. Winning Imperative for Anomaly Detection Market

Companies Mentioned

  • Amazon Web Services, Inc.
  • Broadcom, Inc.
  • Cisco Systems, Inc.
  • Dell Technologies, Inc.
  • Dynatrace, Inc.
  • Happiest Minds Technologies Limited
  • Hewlett Packard Enterprise Company
  • IBM Corporation
  • Microsoft Corporation
  • SAS Institute, Inc.

Methodology

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