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The technologies in IT operations analytics has undergone significant change in recent years, with traditional operation research to advanced machine learning. The rising wave of new technologies, such as machine learning and predictive analytics are creating significant potential in infrastructure management and network & security management applications, and driving the demand for IT operations analytics.

In IT operations analytics market, various technologies, such as visual analytics, machine-based learning, predictive analytics, user-behavior analytics, and root-cause analytics are used in various applications for retrieve, analyze, and report data for IT operations. Increasing IT operations data and advancements in bring your own device (BYOD) & Internet of Things (IOT) are creating new opportunities for various IT operations analytics technologies.
Some of the latest technological developments by various countries in the IT operations analytics (ITOA) market are as follows:
  • United States: Splunk are leading initiatives in machine-based learning and predictive analytics for IT operations. Initiatives include the integration of AI-driven algorithms into their platforms to automate troubleshooting and anomaly detection in IT infrastructure.
  • India: Tata Consultancy Services (TCS) and Infosys are investing in visual analytics and user-behavior analytics solutions for IT operations. Announcements include the development of customizable dashboards and advanced reporting tools for real-time performance monitoring.
  • Germany: SAP SE are pioneering root-cause analytics solutions for IT operations. Initiatives include the integration of advanced analytics engines with IT monitoring tools to identify underlying issues and prevent service disruptions.
  • United Kingdom: Micro Focus International are driving advancements in predictive analytics and machine-based learning for IT operations. Initiatives include the development of AI-powered anomaly detection algorithms to proactively identify and resolve IT incidents.
This report analyzes technology maturity, degree of disruption, competitive intensity, market potential, and other parameters of various technologies in the IT operations analytics (ITOA) market. Some insights are depicted below by a sample figure. For more details on figures, the companies researched, and other objectives/benefits on this research report, please download the report brochure.


 
ITOA Technology Market

 
ITOA Technology Segments

 
ITOA Technology Heat Map

The study includes technology readiness, competitive intensity, regulatory compliance, disruption potential, trends, forecasts and strategic implications for the global IT operations analytics (ITOA) market by application, technology, and region as follows:

Technology Readiness by Technology Type

Competitive Intensity and Regulatory Compliance

Disruption Potential by Technology Type
 
Trends and Forecasts by Technology Type [$M shipment analysis from 2018 to 2030]:
  • Visual Analytics
  • Machine-Based Learning
  • Predictive Analytics
  • User-Behavior Analytics
  • Root-Cause Analytics

Technology Trends and Forecasts by Application [$M shipment analysis from 2018 to 2030]:
  • Real-Time Log Analytics
    • Visual Analytics
    • Machine-Based Learning
    • Predictive Analytics
    • User-Behavior Analytics
    • Root-Cause Analytics
  • Application Performance Management
    • Visual Analytics
    • Machine-Based Learning
    • Predictive Analytics
    • User-Behavior Analytics
    • Root-Cause Analytics
  • Infrastructure Management
    • Visual Analytics
    • Machine-Based Learning
    • Predictive Analytics
    • User-Behavior Analytics
    • Root-Cause Analytics
  • Network and Security Management
    • Visual Analytics
    • Machine-Based Learning
    • Predictive Analytics
    • User-Behavior Analytics
    • Root-Cause Analytics
  • Others
    • Visual Analytics
    • Machine-Based Learning
    • Predictive Analytics
    • User-Behavior Analytics
    • Root-Cause Analytics

Technology Trends and Forecasts by Region [$M shipment analysis for 2018 to 2030]:       
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
  • Asia Pacific
    • Japan
    • China
    • South Korea
    • India
  • The Rest of the World
 
Latest Developments and Innovations in the IT Operations Analytics (ITOA) Technologies

Companies / Ecosystems

Strategic Opportunities by Technology Type

Some of the IT operations analytics (ITOA) companies profiled in this report include Oracle Corporation, IBM Corporation, Hewlett Packard Enterprise Company, Splunk, Microsoft Corporation, Evolven Software, ExtraHop Networks, VMware, and Prelert.
Below are the latest technological developments from top companies in the IT operations analytics (ITOA) market:
  • Splunk introduces Splunk Observability Cloud, a comprehensive platform that leverages visual analytics to provide real-time insights into IT infrastructure performance and application behavior. The platform enables IT teams to visualize complex data sets and identify trends, anomalies, and opportunities for optimization.
  • Dynatrace launches Davis AI, an advanced machine learning engine embedded in its platform that autonomously detects and resolves IT issues in real-time. Davis AI analyzes vast amounts of data to identify patterns and anomalies, enabling proactive problem resolution and optimization of IT operations.
  • IBM announces IBM Cloud Pak for Watson AIOps, a platform that utilizes predictive analytics to anticipate and prevent IT incidents before they occur. By applying AI and machine learning algorithms to historical data, the platform identifies potential issues and provides actionable insights to IT teams.
  • Cisco Systems unveils Cisco SecureX, a cloud-native security platform that incorporates user-behavior analytics to detect and respond to security threats in IT environments. By analyzing user activity and behavior, SecureX enhances threat visibility and enables rapid incident response.
This report answers following 9 key questions:
Q.1 What are some of the most promising and high-growth technology opportunities for the IT operations analytics (ITOA) market?
Q.2 Which technology will grow at a faster pace and why?
Q.3 What are the key factors affecting dynamics of different technologies? What are the drivers and challenges of these technologies in IT operations analytics (ITOA) market?
Q.4 What are the levels of technology readiness, competitive intensity and regulatory compliance in this technology space?
Q.5 What are the business risks and threats to these technologies in IT operations analytics (ITOA) market?
Q.6 What are the latest developments in IT operations analytics (ITOA) technologies? Which companies are leading these developments? 
Q.7 Which technologies have potential of disruption in this market?
Q.8 Who are the major players in this IT operations analytics (ITOA) market? What strategic initiatives are being implemented by key players for business growth?
Q.9 What are strategic growth opportunities in this IT operations analytics (ITOA) technology space?
Table of Contents

1. Executive Summary

2. Technology Landscape
2.1. Technology Background and Evolution
2.2. Technology and Application Mapping
2.3. Supply Chain

3. Technology Readiness
3.1. Technology Commercialization and Readiness
3.2. Drivers and Challenges in IT Operations Analytics (ITOA) Technologies
3.3. Competitive Intensity
3.4. Regulatory Compliance  

4. Technology Trends and Forecasts Analysis from 2018-2030
4.1. IT Operations Analytics (ITOA) Opportunity
4.2. Technology Trends (2018-2023) and Forecasts (2024-2030)
4.2.1. Visual Analytics
4.2.2. Machine-Based Learning
4.2.3. Predictive Analytics
4.2.4. User-Behavior Analytics
4.2.5. Root-Cause Analytics
4.3. Technology Trends (2018-2023) and Forecasts (2024-2030) by Application Segments
4.3.1. Real-Time Log Analytics
4.3.1.1. Visual Analytics
4.3.1.2. Machine-Based Learning
4.3.1.3. Predictive Analytics
4.3.1.4. User-Behavior Analytics
4.3.1.5. Root-Cause Analytics
4.3.2. Application Performance Management
4.3.2.1. Visual Analytics
4.3.2.2. Machine-Based Learning
4.3.2.3. Predictive Analytics
4.3.2.4. User-Behavior Analytics
4.3.2.5. Root-Cause Analytics
4.3.3. Infrastructure Management
4.3.3.1. Visual Analytics
4.3.3.2. Machine-Based Learning
4.3.3.3. Predictive Analytics
4.3.3.4. User-Behavior Analytics
4.3.3.5. Root-Cause Analytics
4.3.4. Network and Security Management
4.3.4.1. Visual Analytics
4.3.4.2. Machine-Based Learning
4.3.4.3. Predictive Analytics
4.3.4.4. User-Behavior Analytics
4.3.4.5. Root-Cause Analytics
4.3.5. Others
4.3.5.1. Visual Analytics
4.3.5.2. Machine-Based Learning
4.3.5.3. Predictive Analytics
4.3.5.4. User-Behavior Analytics
4.3.5.5. Root-Cause Analytics

5. Technology Opportunities (2018-2030) by Region
5.1. IT Operations Analytics (ITOA) Market by Region
5.2. North American IT Operations Analytics (ITOA) Technology Market
5.2.1. United States IT Operations Analytics (ITOA) Technology Market
5.2.2. Canadian IT Operations Analytics (ITOA) Technology Market
5.2.3. Mexican IT Operations Analytics (ITOA) Technology Market
5.3. European IT Operations Analytics (ITOA) Technology Market
5.3.1. The United Kingdom IT Operations Analytics (ITOA) Technology Market
5.3.2. German IT Operations Analytics (ITOA) Technology Market
5.3.3. French IT Operations Analytics (ITOA) Technology Market
5.4. APAC IT Operations Analytics (ITOA) Technology Market
5.4.1. Chinese IT Operations Analytics (ITOA) Technology Market
5.4.2. Japanese IT Operations Analytics (ITOA) Technology Market
5.4.3. Indian IT Operations Analytics (ITOA) Technology Market
5.4.4. South Korean IT Operations Analytics (ITOA) Technology Market
5.5. ROW IT Operations Analytics (ITOA) Technology Market

6. Latest Developments and Innovations  in the IT Operations Analytics (ITOA) Technologies

7. Companies / Ecosystem
7.1. Product Portfolio Analysis
7.2. Market Share Analysis
7.3. Geographical Reach
 
8. Strategic Implications
8.1. Implications
8.2. Growth Opportunity Analysis
8.2.1. Growth Opportunities Analysis by Technology
8.2.2. Growth Opportunities Analysis by Application
8.2.3. Growth Opportunities Analysis by Region
8.3. Emerging Trends in the IT Operations Analytics (ITOA) Market
8.4. Disruption Potential
8.5. Strategic Analysis
8.5.1. New Product Development
8.5.2. Capacity Expansion of the IT Operations Analytics (ITOA) Market
8.5.3. Mergers, Acquisitions, and Joint Ventures in the IT Operations Analytics (ITOA) Market
 
9. Company Profiles of Leading Players
9.1. Oracle Corporation
9.2. IBM Corporation
9.3. Hewlett Packard Enterprise Company
9.4. Splunk, Microsoft Corporation
9.5. Evolven Software
9.6. ExtraHop Networks
9.7. VMware
9.8. Prelert
.

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Lucintel has been in the business of market research and management consulting since 2000 and has published over 1000 market intelligence reports in various markets / applications and served over 1,000 clients worldwide. This study is a culmination of four months of full-time effort performed by Lucintel's analyst team. The analysts used the following sources for the creation and completion of this valuable report:
  • In-depth interviews of the major players in this market
  • Detailed secondary research from competitors’ financial statements and published data 
  • Extensive searches of published works, market, and database information pertaining to industry news, company press releases, and customer intentions
  • A compilation of the experiences, judgments, and insights of Lucintel’s professionals, who have analyzed and tracked this market over the years.
Extensive research and interviews are conducted across the supply chain of this market to estimate market share, market size, trends, drivers, challenges, and forecasts. Below is a brief summary of the primary interviews that were conducted by job function for this report.
 
Thus, Lucintel compiles vast amounts of data from numerous sources, validates the integrity of that data, and performs a comprehensive analysis. Lucintel then organizes the data, its findings, and insights into a concise report designed to support the strategic decision-making process. The figure below is a graphical representation of Lucintel’s research process. 
 

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