Cognitive Operations Market Opportunities, Size, Share, Global Trends and Fast Forward Research 2023

 The report "Cognitive Operations Market by Component (Solutions and Services), Application (ITOA, APM, Infrastructure Management, Network Analytics, and Security Analytics), Deployment Mode, Enterprise Size, Vertical, and Region - Global Forecast to 2023", The global cognitive operations market size is expected to grow from USD 7.27 billion in 2018 to USD 21.67 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 24.4% during the forecast period. Major growth factors for the cognitive operations market include a growing need to monitor the complex IT environment, and an increasing focus on the adoption of cloud-based cognitive IT operations solutions. A growing need to deliver an enhanced customer experience and an increasing need to analyze growing IT operations data will provide significant growth opportunities for vendors in the market.

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Top Key Players

Major vendors in the global cognitive operations market include IBM (US), Splunk (US), CA Technologies (US), Micro Focus (UK), VMware (US), HCL Technologies (India), AppDynamics (US), BMC Software (US), New Relic (US), Appnomic  (India), CloudFabrix (US), Loom Systems (US), Dynatrace (US), Zenoss (US), Ymor (US), Devo (US), Logz.io (US),  ServiceNow (US), Corvil (Ireland), Interlink Software Services (UK), Correlata (Israel), ScienceLogic (US), Sumo Logic (US), RISC Networks (US), and Bay Dynamics (US).

Increasing need to analyze growing IT operations data

Nowadays, data across IT departments is growing at a rapid pace. Furthermore, digital transformation is also contributing to the generation of large volumes of data, including events data, log data, performance data, and configuration data. IT operations managers can use this data to enhance their operational efficiency and streamline business operations. IT analytics solutions coupled with cognitive capabilities can play a crucial role in solving various problems. For instance, analytics solutions can find data patterns, and cognitive capabilities such as machine learning can be applied on data patterns to generate insights. Therefore, machine learning algorithms can be useful to assess data and respond to this data in the IT operations environment, which would further help save time and money by automating and managing issues that occur in the IT operations environment.

Constantly changing IT operations environment

IT operations management requires IT managers to keep a track of capacity, performance, and availability of the IT infrastructure. Small changes in the systems can majorly affect the performance of IT systems and the overall performance. Moreover, unexpected changes may disrupt the functioning of applications, which needs to be resolved quickly to prevent losses. Additionally, with the growth in adoption containers, virtualized technologies, and cloud, the IT operations environment is changing drastically. Apart from that, after shifting their legacy on-premises environment to the cloud, organizations are relying on on-premises data centers, public cloud resources, and private cloud deployments. This constantly changing IT operations environment may become a challenge for successfully implementing cognitive operations solutions.

By component

Solutions

Software Tools

Platform

Services

Deployment and integration

Support and maintenance

Training and consulting

By deployment mode

Cloud

On-premises

Cognitive Operations Market By application

IT Operations Analytics

Application Performance Management

Infrastructure Management 

Network Analytics

Security analytics

Others (Log and Event Management, Predictive Maintenance, Anomaly Detection, App Experience Analytics, and Root Cause Analytics)

By enterprise size

Large Enterprises

SMEs

By vertical

BFSI

Healthcare and Life Sciences

BFSI

IT and telecom

Retail and eCommerce

Manufacturing

Government

Media and Entertainment

Others (Energy and Utilities, Transportation and Logistics, and Education)

By region

North America

Europe

Asia Pacific (APAC)

Rest of the World (RoW)

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