Network Analytics Market - Forecasts from 2023 to 2028

The Network Analytics market is estimated to grow at a CAGR of 22.5% during the forecast period.

Network analytics refers to the process of examining and interpreting data collected from computer networks to gain insights into their performance, security, and overall functioning. It involves analyzing network traffic patterns, identifying potential bottlenecks, detecting anomalies or security threats, and optimizing network infrastructure. By leveraging various techniques such as data mining, machine learning, and statistical analysis, network analytics helps organizations make informed decisions, enhance network efficiency, and ensure the reliability and resilience of their network infrastructure.

Introduction:

The network analytics market refers to the industry that offers technologies and solutions focused on analyzing and optimizing computer networks. It involves examining network data to gain insights into performance, security, and efficiency, allowing organizations to make informed decisions and improve their network infrastructure. The market is driven by factors such as the rising demand for network visibility, the increasing adoption of cloud computing, and the growing complexity of network environments. It caters to various sectors including telecommunications, banking, healthcare, manufacturing, and IT services, among others, helping them enhance network performance, detect threats, and ensure a smooth and secure network operation.

Drivers:

• Increasing Adoption of Cloud Computing:

The rapid adoption of cloud computing services drives the demand for network analytics solutions to optimize performance, monitor cloud-based networks, and ensure efficient utilization of cloud resources.

• Proliferation of Internet of Things (IoT) Devices:

The exponential growth of IoT devices, such as smart sensors and connected devices, generates massive amounts of network data. Network analytics tools help organizations manage and analyze this data effectively, enabling insights for improved decision-making and operational efficiency.

• Network Visibility and Threat Detection:

With the growing complexity and sophistication of cyber threats, organizations require robust network analytics solutions for comprehensive network visibility and advanced threat detection capabilities. This includes identifying anomalies, detecting potential security breaches, and enabling timely response and mitigation.

• Network Performance Optimization:

Network analytics solutions play a crucial role in optimizing network performance. They help organizations identify and address bottlenecks, latency issues, and bandwidth constraints, ensuring efficient network operations and delivering a seamless user experience.

• Digital Transformation Initiatives:

In the era of digital transformation, organizations rely on network analytics to support their initiatives. By leveraging analytics capabilities, businesses can ensure scalability, agility, and smooth migration to digital platforms, thereby enhancing their competitiveness in the digital landscape.

• Network Security Enhancement:

Network analytics solutions are essential for enhancing network security. They enable real-time monitoring, threat intelligence, and proactive identification of security vulnerabilities, helping organizations prevent and mitigate potential cyber threats.

• Demand for Real-Time Network Monitoring:

Real-time network monitoring is critical for organizations to identify and resolve network issues promptly. Network analytics solutions provide comprehensive monitoring, diagnostics, and reporting capabilities in real-time, ensuring optimal network performance and reducing downtime.

• Growth of Big Data Analytics:

The increasing volume, velocity, and variety of network data require robust big data analytics capabilities. Network analytics solutions enable organizations to extract valuable insights from the vast amount of network data, leading to informed decision-making, proactive network management, and improved operational efficiency.

• Increasing Network Complexity:

With the advent of technologies like hybrid networks, multi-cloud environments, and software-defined networking (SDN), network infrastructure has become more complex. Network analytics solutions help organizations manage and optimize this complex environment by providing visibility, control, and automation capabilities.

• Regulatory Compliance Requirements:

Industries such as finance, healthcare, and telecommunications face stringent regulatory compliance standards. Network analytics solutions assist in ensuring compliance, data privacy, and network security by providing monitoring, auditing, and reporting capabilities that align with regulatory requirements.

Products offered by key companies:

• Cisco Green Network Analytics:Cisco's Green Network Analytics is a suite of tools that helps organizations to reduce their environmental impact by optimizing their network infrastructure. The suite includes tools for monitoring energy consumption, identifying areas where energy can be saved, and reporting on environmental performance.
• IBM Cloud Pak for Network Automation:IBM's Cloud Pak for Network Automation is a cloud-based platform that helps organizations to automate their network operations. The platform includes a number of features that help to reduce the environmental impact of network operations, such as the ability to schedule network changes during off-peak hours and the ability to track the carbon footprint of network operations.
• Juniper Networks Contrail Green:Juniper Networks Contrail Green is a software-defined networking (SDN) solution that helps organizations to reduce their environmental impact. The solution includes features for optimizing network traffic, reducing power consumption, and improving cooling efficiency.
• Palo Alto Networks Cortex XDR:Palo Alto Networks Cortex XDR is a security analytics platform that helps organizations to detect and respond to threats. The platform includes a number of features that help to reduce the environmental impact of security operations, such as the ability to analyze security data in the cloud and the ability to use machine learning to identify threats.

Positive growth in the cloud-based deployment model segment:

The cloud-based deployment model is experiencing positive growth in the network analytics market. This is due to its scalability and flexibility, allowing organizations to easily scale their network analytics infrastructure based on demand. Additionally, cloud-based deployment eliminates the need for on-premises hardware and reduces maintenance costs, making it an attractive option for businesses looking for cost-effective and agile network analytics solutions.

The North American region is anticipated to hold a significant share:

North America is expected to hold a significant share in the network analytics market. This can be attributed to several factors such as the presence of established technology providers, the high adoption of advanced networking technologies in industries like telecommunications and IT, and the increasing emphasis on network security and optimization. Additionally, the region has a strong digital infrastructure and a high level of awareness about the benefits of network analytics, which drives the demand for innovative solutions and contributes to North America's prominent position in the network analytics market.

Key developments:

• In Dec 2022,Oracle Communications has launched the Oracle Network Analytics Data Director, the second application in their Network Analytics portfolio, to support the evolution of 5G operations. As 5G networks become more complex and require insights-driven automation, the Data Director enables operators to flexibly integrate their 5G core into existing operational tools, even if those tools are not provided by Oracle.
• In Feb 2023, Nokia has launched AVA Customer and Mobile Network Insights, a cloud-native analytics software solution that simplifies the collection and analysis of 5G network data for communication service providers (CSPs). The solution utilizes AI and machine learning to enable intelligent decision making and improve operational efficiency, network performance, and customer experience.

Key Segments:

By Deployment Model

• On-Premise
• On-Cloud

By End-User Industry

• Cloud Service Provider
• Managed Service Provider
• Telecom Provider
• Others

By Application

• Customer Analysis
• Risk Management And Fault Detection
• Network Performance Management
• Compliance Management
• Quality Management
• Others

By Geography

• North America
• United States
• Canada
• Mexico
• South America
• Brazil
• Argentina
• Others
• Europe
• United Kingdom
• Germany
• France
• Italy
• Spain
• Others
• Middle East and Africa
• Saudi Arabia
• UAE
• Others
• Asia Pacific
• Japan
• China
• India
• South Korea
• Taiwan
• Thailand
• Indonesia
• Others