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IT運用プラットフォーム向け人工知能の世界市場（2024年～2031年）

Global Artificial Intelligence For IT Operations Platform Market - 2024-2031

出版日
ページ情報
英文 204 Pages
納期
即日から翌営業日
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=144.06円
IT運用プラットフォーム向け人工知能の世界市場（2024年～2031年）
出版日: 2024年12月30日
発行: DataM Intelligence
ページ情報: 英文 204 Pages
納期: 即日から翌営業日
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概要

世界のIT運用プラットフォーム向け人工知能の市場規模は、2023年に15億9,000万米ドルに達し、2031年には85億9,000万米ドルに達すると予測され、予測期間2024年～2031年のCAGRは23.47％で成長する見込みです。

AIOpsソリューションは、機械学習、ビッグデータ分析、自動化を採用してIT運用を最適化し、リアルタイムの監視、異常の特定、プロアクティブな問題解決を促進します。IT環境の複雑化が進むとともに、迅速かつ的確な問題解決が求められるようになったことで、銀行、ヘルスケア、小売、製造など、さまざまな分野でAIOpsソリューションの導入が加速しています。

国際的な営利団体における迅速なデジタル革命により、データセットはますます複雑になり、データ処理に多大な時間、費用、労力が必要になっています。ITオペレーションがこのような変化を遂げる中、ITチームはビジネスオペレーションを維持するために複雑なデータセットを管理するという問題に直面しています。NetBase Quidが2023年のAI Index Reportで報告しているように、人工知能に対する企業の年間投資額は、様々な業界における提携や買収に基づき、2021年には1,196億6,000万米ドル、2022年には771億7,000万米ドルと推定されています。

デジタル革新に対する需要の高まりと、ソリューションの精度と効率を向上させるための企業投資の拡大が、この分野におけるこれらのツールの需要を促進しています。米国、カナダ、メキシコには、Amazon Web Services, Inc.、IBM Corporation、Dynatrace LLC、BMC Software, Inc.、Dell Inc.など、IT運用ツールの著名な人工知能プロバイダーが存在するため、予測期間中、北米のAIOps市場の成長が促進されます。

力学

デジタルオペレーションの変革

AIOpsは、デジタル時代の高まる要求を満たすためにIT運用を強化することで、デジタルトランスフォーメーションを変革しています。この革新的なテクノロジーは、バックエンドプロセスを最適化し、複雑なITインフラの管理を合理化することで、シームレスなデジタル体験の提供を可能にします。ハイブリッド・クラウドのエコシステム内でインフラ、アプリケーション、サービスを効率的に調整し、有効性と顧客満足度の向上を保証します。

世界企業がリモートワークとコラボレーションの流行後の状況でデジタルトランスフォーメーションに取り組む中、多くの組織がテクノロジー統合の複雑さのために目標を実現する上で困難に遭遇しています。AIOpsテクノロジーは、機械学習を採用して業務データを文脈化し、問題解決を自動化し、情報に基づいた意思決定を促進することで、こうした課題を軽減します。このソリューションは、変革プロセスを最適化し、組織の効果的なスケーリングを促進します。

2022年のIBMの調査によると、54％の企業が全業種にわたってAI適用のメリットを実感しています。AIの導入により、ITまたはネットワーク運用の有効性が向上し（53%）、効率性の向上により経費が削減され、顧客の幸福度が高まっています（48%）。

セキュリティとコンプライアンスの強化

セキュリティの脅威に対処し、規制基準に準拠する必要性が高まっていることが、AIOpsプラットフォームの採用を後押ししています。IT環境がますます複雑化し、サイバー脅威がより高度になるにつれ、企業は規制コンプライアンスを維持しながら、セキュリティ侵害を検知し、対応するという課題に直面しています。AIOpsプラットフォームは、ログ、イベント、ネットワーク・トラフィックなどの膨大なセキュリティ・データを調査することで、高度な分析と機械学習アルゴリズムを活用し、セキュリティ運用を強化します。

このテクノロジーは、リアルタイムの異常検知とプロアクティブな脅威識別を実現し、迅速なインシデント対応と侵害リスクの低減を可能にします。AIOpsシステムは、セキュリティデータの収集、分析、報告を自動化することで、コンプライアンスを強化します。継続的な監視、監査証跡の作成、業界要件への準拠を支援します。

AIOpsプラットフォームは、AIと自動化を統合することで、セキュリティ管理を強化し、重要な資産を保護し、業務効率を向上させます。2024年2月、Metra Groupは、高度な分析とAI/ML機能を活用してGCC諸国全体のデジタルトランスフォーメーションとセキュリティを強化するため、インドを拠点とするIT運用のための安全な人工知能のプロバイダーであるTechBridge Consultancy Services LLPとの付加価値パートナーシップを発表しました。

AIOpsアルゴリズムの不透明性

透明性の欠如は、意思決定プロセスにおける信頼と理解を侵食します。責任とコンプライアンスが不可欠な金融やヘルスケアなどの規制の厳しい業界では、オープン性の欠如が特に憂慮されます。これらのアルゴリズムは複雑であるため、その検証や結果の解釈が複雑になることが多く、信頼性や公平性に関する疑問が生じます。これらの困難を克服するためには、ロバスト性のある解釈可能性ツールの開発が必要です。

この戦略では、AIOpsシステムを解明し、その意思決定プロセスに対する透明性の高い洞察を提供することを目指します。組織は、オープン性を促進することで、信頼を培い、規制遵守を保証し、AIが生成する提案の背後にある理由の理解を高めることができます。AIOpsシステムの信頼を醸成するには、アルゴリズムの複雑さと解釈可能性のバランスを取ることが不可欠です。この均衡を保つことは、受容を促進するだけでなく、人間の判断が重要な分野での説明責任と公開性という本質的な原則を強化します。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • デジタルオペレーションの変革
      • セキュリティとコンプライアンスの強化
    • 抑制要因
      • AIOpsアルゴリズムの不透明性
    • 機会
    • 影響分析

第5章 産業分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 規制分析
  • DMIの見解

第6章 提供別

  • プラットフォーム
  • ドメイン中心
    • 監視中心のAIOps
    • ITSM中心のAIOps
    • データレイク中心のAIOps
  • ドメイン非依存
  • サービス
    • プロフェッショナルサービス
    • マネージドサービス

第7章 用途別

  • インフラストラクチャ管理
  • アプリケーションパフォーマンス分析
  • リアルタイム分析
  • ネットワークとセキュリティ管理
  • その他

第8章 展開別

  • クラウド
  • オンプレミス

第9章 組織規模別

  • 大企業
  • 中小企業

第10章 エンドユーザー別

  • IT・通信
  • 小売・eコマース
  • エネルギー・公益事業
  • メディア・エンターテイメント
  • BFSI
  • ヘルスケア・ライフサイエンス
  • 政府・防衛
  • 運輸・物流
  • 製造
  • その他

第11章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • イタリア
    • スペイン
    • その他欧州
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋
    • 中国
    • インド
    • 日本
    • オーストラリア
    • その他アジア太平洋
  • 中東・アフリカ

第12章 競合情勢

  • 競合シナリオ
  • 市況・シェア分析
  • M&A分析

第13章 企業プロファイル

  • APPDYNAMICS
    • 会社概要
    • 製品ポートフォリオと概要
    • 財務概要
    • 主な発展
  • BMC Software, Inc.
  • Broadcom Inc.
  • HCL Technologies Limited
  • IBM Corporation
  • Micro Focus International plc
  • Dell Inc.
  • ProphetStor Data Services, Inc.
  • Splunk LLC
  • Thales

第14章 付録

目次
Product Code: ICT8870

Global Artificial Intelligence for IT Operations Platform Market reached US$ 1.59 billion in 2023 and is expected to reach US$ 8.59 billion by 2031, growing with a CAGR of 23.47% during the forecast period 2024-2031.

AIOps solutions employ machine learning, big data analytics and automation to optimize IT operations, facilitating real-time monitoring, anomaly identification and proactive issue resolution. The increasing intricacy of IT environments, along with the demand for expedited and precise problem resolution, has hastened the implementation of AIOps solutions across diverse sectors, including banking, healthcare, retail and manufacturing.

The swift digital revolution in international commercial entities has resulted in increasingly intricate datasets, necessitating substantial time, expense and effort for data processing. As IT operations undergo this change, IT teams encounter the issue of managing complex datasets to maintain business operations. As reported by NetBase Quid in the AI Index Report of 2023, the annual corporate investment in artificial intelligence was estimated at US$ 119.66 billion in 2021 and US$ 77.17 billion in 2022, based on collaborations and acquisitions across various industries.

The increasing demand for digital innovations and escalating corporate investments to improve the precision and efficiency of solutions are propelling the demand for these tools in the area. The presence of prominent artificial intelligence for IT operations tool providers, including Amazon Web Services, Inc., IBM Corporation, Dynatrace LLC, BMC Software, Inc. and Dell Inc., in US, Canada and Mexico will enhance the growth of the AIOps market in North America during the forecast period.

Dynamics

Transforming Digital Operations

AIOps is transforming digital transformation by enhancing IT operations to satisfy the growing demands of the digital age. This innovative technology enables the provision of seamless digital experiences by optimizing backend processes and streamlining the management of intricate IT infrastructures. It efficiently coordinates infrastructure, applications and services inside hybrid cloud ecosystems, guaranteeing effectiveness and improved customer satisfaction.

As global firms engage in digital transformation in the post-pandemic landscape of remote work and collaboration, numerous organizations encounter difficulties in realizing their goals due to the intricacies of technology integration. AIOps technologies mitigate these challenges by employing machine learning to contextualize operational data, automate problem resolution and facilitate informed decision-making. The solutions optimize transformation processes and facilitate effective organizational scaling.

A 2022 IBM survey indicated that 54% of enterprises have seen the benefits of AI application across all industries. The implementation of AI enhances the efficacy of IT or network operations (53%), decreases expenses through heightened efficiency and elevates customer happiness (48%).

Enhancing Security and Compliance

The increasing need to address security threats and comply with regulatory standards is driving the adoption of AIOps platforms. As IT environments become increasingly intricate and cyber threats more advanced organizations face challenges in detecting and responding to security breaches while maintaining regulatory compliance. AIOps platforms utilize sophisticated analytics and machine learning algorithms to enhance security operations by examining vast amounts of security data, including logs, events and network traffic.

The technologies provide real-time anomaly detection and proactive threat identification, enabling swift incident response and reducing the risk of breaches. AIOps systems enhance compliance by automating the collection, analysis and reporting of security data. They offer ongoing surveillance, create audit trails and assist firms in complying with industry requirements.

AIOps platforms increase security management, protect vital assets and improve operational efficiency by integrating AI and automation, enabling enterprises to efficiently traverse the dynamic security landscape. In February 2024, Metra Group announced a value-added partnership with TechBridge Consultancy Services LLP, an India-based provider of secure artificial intelligence for IT operations, to enhance digital transformation and security across GCC countries utilizing advanced analytics and AI/ML capabilities.

The Opacity of AIOps Algorithms

The lack of transparency eroding confidence and understanding in decision-making processes. The absence of openness is particularly alarming in heavily regulated industries like finance and healthcare, where responsibility and compliance are essential. The intricacy of these algorithms frequently complicates the validation and interpretation of their results, hence eliciting questions regarding their trustworthiness and equity. Developing robust interpretability tools is necessary to overcome these difficulties.

The strategies seek to elucidate AIOps systems, providing transparent insights into their decision-making processes. Organizations may cultivate trust, guarantee regulatory adherence and enhance comprehension of the reasoning behind AI-generated suggestions by promoting openness. Achieving a balance between algorithmic complexity and interpretability is essential for fostering trust in AIOps systems. Attaining this equilibrium not only fosters acceptance but also strengthens the essential principles of accountability and openness in sectors where human judgment is crucial..

Segment Analysis

The global artificial intelligence for IT operations platform market is segmented based on offering, application, deployment organization size, end-user and region.

Driving IT Efficiency With Platforms

AIOps platforms amalgamate many features, such as event correlation, anomaly detection and automated issue response, offering a comprehensive strategy for IT operations. This integration allows IT teams to enhance visibility and proactively oversee intricate hybrid and multi-cloud settings. Platforms enable the use of machine learning, big data analytics and automation, optimizing workflows and minimizing expenses. The capacity of these platforms to scale according to evolving IT requirements has increased their demand, as enterprises pursue solutions that facilitate digital transformation and enhance operational efficiency.

In March 2024, Visionet Systems Inc., a technology service provider, established a cooperation with Algomox, a provider of artificial intelligence for IT operations, to facilitate digital transformations in Visionet's ITOps operations. The incorporation of Algomox's AIOps platform into Visionet's managed cloud services automates intricate IT activities utilizing advanced AI technology, provides profound operational data insights and guarantees dependable service delivery.

Geographical Penetration

Advanced IT Infrastructure, Industry Demand, Real-Time Analytics and Digital Transformation in North America

North America comprises numerous prominent technology firms and sophisticated IT infrastructures, enabling the prompt implementation of cutting-edge AIOps solutions. The proliferation of numerous firms in diverse sectors, including finance, healthcare and retail, propels the necessity for effective IT operations and proactive incident management.

The escalating complexity of IT environments and the demand for real-time data analytics are driving the expansion of AIOps platforms in North America. Significant investments in research and development by major entities, coupled with a proficient staff, further enhance the United States' predominant share in the AIOps market. Moreover, the emphasis on digital transformation programs and cloud adoption among US enterprises amplifies the demand for scalable AIOps solutions.

Competitive Landscape

The major global players in the market include APPDYNAMICS, BMC Software, Inc., Broadcom Inc., HCL Technologies Limited, IBM Corporation, Micro Focus International plc, Dell Inc., ProphetStor Data Services, Inc., Splunk LLC and Thales.

Sustainability Analysis

Conventional IT operations encounter significant environmental issues, especially due to the energy consumption of data centers that frequently depend on non-renewable energy sources, resulting in elevated carbon emissions. The persistent need for hardware upgrades produces electronic waste, which presents environmental hazards if not disposed of properly. Manual IT processes are resource-intensive, resulting in inefficiencies and waste. As sustainability gains prominence, firms that use eco-friendly IT strategies not only diminish their environmental impact but also secure competitive advantages, enhance operational efficiencies and bolster future resilience against resource scarcity and stringent laws.

AIOps provides an effective solution to these difficulties by enhancing IT operations for sustainability. AIOps platforms utilize predictive analytics and automation to optimize resource allocation, reduce energy usage and prolong the longevity of IT infrastructure. AIOps tools can identify problems promptly, averting energy-consuming downtimes and superfluous resource expenditure. Moreover, by automating repetitive processes, AIOps diminishes the necessity for manual interventions, hence reducing operational inefficiencies.

Its capacity for dynamic resource adjustment via auto-scaling and self-healing mechanisms guarantees optimal resource usage, resulting in substantial energy savings. As AIOps platforms advance, they will be pivotal in advancing sustainability objectives, potentially minimizing e-waste and enhancing operations for more environmentally friendly IT practices, establishing AIOps as a fundamental element of future green IT endeavors.

Digital Transformation

AIOps (Artificial Intelligence for IT Operations) is emerging as a crucial facilitator of digital transformation across several industries. As enterprises increasingly depend on data-driven decision-making, AIOps offers essential solutions to enhance data management via automation. AIOps solutions facilitate the efficient management of data gathering, processing, analysis and visualization, enabling enterprises to discern critical insights in real time, hence maintaining competitiveness in a progressively intricate digital environment.

AIOps significantly enhances customer experience using sophisticated data analytics. Utilizing AI and machine learning enables organizations to acquire profound insights into client behavior, facilitating the customization of their products and services. AIOps facilitates product and service differentiation, bolstering brand loyalty and increasing income. Monitoring and observability capabilities guarantee a flawless customer engagement, proactively correcting issues and enhancing brand value.

AIOps mitigates interruptions by automating manual operations, hence decreasing bottlenecks and downtime. This automation promotes operational resilience and increases productivity across departments. AIOps' capacity to forecast possible problems with predictive algorithms enables enterprises to tackle challenges preemptively, hence ensuring seamless and uninterrupted operations.

By Offering

  • Platform
  • Domain-Centric
    • Monitoring-centric AIOps
    • ITSM centric-AIOps
    • Data-Lake centric-AIOps
  • Domain-Agnostic
  • Services
    • Professional Services
    • Managed Services

By Application

  • Infrastructure Management
  • Application Performance Analysis
  • Real-Time Analytics
  • Network & Security Management
  • Others

By Deployment

  • Cloud
  • On-premises

By Organization Size

  • Large Enterprises
  • SMEs

By End-User

  • IT & Telecom
  • Retail & E-Commerce
  • Energy & Utilities
  • Media & Entertainment
  • BFSI
  • Healthcare & Life Sciences
  • Government & Defense
  • Transportation and Logistics
  • Manufacturing
  • Others

By Region

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • France
    • Italy
    • Spain
    • Rest of Europe
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia-Pacific
    • China
    • India
    • Japan
    • Australia
    • Rest of Asia-Pacific
  • Middle East and Africa

Key Developments

  • In September 2024, Vitria Technology, Inc., the architect of the VIA AIOps platform-an agile AI solution tailored for extensive operational intelligence-reported a significant increase in demand and customer acceptance. In the past year, Vitria Technology's AIOps platform facilitated a 60% enhancement in overall service availability, an 80% decrease in the time needed to handle service issues and 92% of incidents were identified prior to affecting consumers.
  • In April 2024, BMC, a software solution provider, purchased Netreo, a provider of intelligent and secure IT network and application solutions, to enhance its leadership in observability and artificial intelligence for IT operations. BMC intends to enhance visibility into company operational performance across infrastructure, networks and apps via an open observability platform through this acquisition.
  • In September 2023, Viavi Solutions Inc. established a relationship with Google Cloud to introduce NITRO AIOps, a cloud-based network intelligence and optimization solution. This collaboration sought to address significant difficulties faced by communication service providers (CSPs) and investigate new avenues for network optimization and intelligence.
  • In January 2023, Interlink Software collaborated with Cisco to integrate their AIOps platform with AppDynamics. Through this integration, IT teams reduce the risk of avoidable outages and improve service availability, hence optimizing overall operational performance.

Why Purchase the Report?

  • To visualize the global artificial intelligence for IT operations platform market segmentation based on offering, application, deployment organization size, end-user and region, as well as understand key commercial assets and players.
  • Identify commercial opportunities by analyzing trends and co-development.
  • Excel data sheet with numerous data points of the artificial intelligence for IT operations platform market-level with all segments.
  • PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
  • Product mapping available as excel consisting of key products of all the major players.

The global artificial intelligence for IT operations platform market report would provide approximately 78 tables, 80 figures and 204 pages.

Target Audience 2024

  • Manufacturers/ Buyers
  • Industry Investors/Investment Bankers
  • Research Professionals
  • Emerging Companies

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Offering
  • 3.2. Snippet by Application
  • 3.3. Snippet by Deployment
  • 3.4. Snippet by Organization Size
  • 3.5. Snippet by End-User
  • 3.6. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Transforming Digital Operations
      • 4.1.1.2. Enhancing Security and Compliance
    • 4.1.2. Restraints
      • 4.1.2.1. The Opacity of AIOps Algorithms
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Regulatory Analysis
  • 5.5. DMI Opinion

6. By Offering

  • 6.1. Introduction
    • 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 6.1.2. Market Attractiveness Index, By Offering
  • 6.2. Platform*
    • 6.2.1. Introduction
    • 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 6.3. Domain-Centric
    • 6.3.1. Monitoring-centric AIOps
    • 6.3.2. ITSM centric-AIOps
    • 6.3.3. Data-Lake centric-AIOps
  • 6.4. Domain-Agnostic
  • 6.5. Services
    • 6.5.1. Professional Services
    • 6.5.2. Managed Services

7. By Application

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 7.1.2. Market Attractiveness Index, By Application
  • 7.2. Infrastructure Management*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Application Performance Analysis
  • 7.4. Real-Time Analytics
  • 7.5. Network & Security Management
  • 7.6. Others

8. By Deployment

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment
    • 8.1.2. Market Attractiveness Index, By Deployment
  • 8.2. Cloud*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. On-premises

9. By Organization Size

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
    • 9.1.2. Market Attractiveness Index, By Organization Size
  • 9.2. Large Enterprises*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. SMEs

10. By End-User

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 10.1.2. Market Attractiveness Index, By End-User
  • 10.2. IT & Telecom*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Retail & E-Commerce
  • 10.4. Energy & Utilities
  • 10.5. Media & Entertainment
  • 10.6. BFSI
  • 10.7. Healthcare & Life Sciences
  • 10.8. Government & Defense
  • 10.9. Transportation and Logistics
  • 10.10. Manufacturing
  • 10.11. Others

11. By Region

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 11.1.2. Market Attractiveness Index, By Region
  • 11.2. North America
    • 11.2.1. Introduction
    • 11.2.2. Key Region-Specific Dynamics
    • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
    • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
    • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.2.8.1. US
      • 11.2.8.2. Canada
      • 11.2.8.3. Mexico
  • 11.3. Europe
    • 11.3.1. Introduction
    • 11.3.2. Key Region-Specific Dynamics
    • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
    • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
    • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.3.8.1. Germany
      • 11.3.8.2. UK
      • 11.3.8.3. France
      • 11.3.8.4. Italy
      • 11.3.8.5. Spain
      • 11.3.8.6. Rest of Europe
  • 11.4. South America
    • 11.4.1. Introduction
    • 11.4.2. Key Region-Specific Dynamics
    • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
    • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
    • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.4.8.1. Brazil
      • 11.4.8.2. Argentina
      • 11.4.8.3. Rest of South America
  • 11.5. Asia-Pacific
    • 11.5.1. Introduction
    • 11.5.2. Key Region-Specific Dynamics
    • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
    • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
    • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.5.8.1. China
      • 11.5.8.2. India
      • 11.5.8.3. Japan
      • 11.5.8.4. Australia
      • 11.5.8.5. Rest of Asia-Pacific
  • 11.6. Middle East and Africa
    • 11.6.1. Introduction
    • 11.6.2. Key Region-Specific Dynamics
    • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Offering
    • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deloyment
    • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
    • 11.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

  • 12.1. Competitive Scenario
  • 12.2. Market Positioning/Share Analysis
  • 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

  • 13.1. APPDYNAMICS*
    • 13.1.1. Company Overview
    • 13.1.2. Product Portfolio and Description
    • 13.1.3. Financial Overview
    • 13.1.4. Key Developments
  • 13.2. BMC Software, Inc.
  • 13.3. Broadcom Inc.
  • 13.4. HCL Technologies Limited
  • 13.5. IBM Corporation
  • 13.6. Micro Focus International plc
  • 13.7. Dell Inc.
  • 13.8. ProphetStor Data Services, Inc.
  • 13.9. Splunk LLC
  • 13.10. Thales

LIST NOT EXHAUSTIVE

14. Appendix

  • 14.1. About Us and Services
  • 14.2. Contact Us