PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1363862
PUBLISHER: Bizwit Research & Consulting LLP | PRODUCT CODE: 1363862
Global Anomaly Detection Market is anticipated to grow with a healthy growth rate of more than 15.30% over the forecast period 2023-2030. Anomaly detection refers to the process of identifying patterns or observations that deviate significantly from the expected behavior or normal patterns within a dataset. It is commonly used in various fields such as finance, cybersecurity, manufacturing, and healthcare to detect unusual or suspicious activities that may indicate fraud, errors, or anomalies. The Anomaly Detection market is expanding because of factors such as the increasing number of connected devices and the growing adoption of machine learning and artificial intelligence. The goal of anomaly detection is to separate normal behavior from abnormal or anomalous behavior. The detection methods, depending on the nature of the data and the specific problem domain. Its importance has progressively increased during the forecast period 2023-2030.
Connected devices continuously collect data from various sources, such as environmental sensors, machine sensors, and wearable devices. Anomaly detection algorithms can analyze this real-time data to identify unusual patterns or deviations from expected behavior. According to Statista, with 17 billion connected devices worldwide in 2030, the consumer sector is expected to dominate in terms of the number of Internet of Things connected devices. Furthermore, the total installed base of Internet of Things connected devices globally is predicted to reach 30.9 billion units by 2025, up from 13.8 billion units in 2021. Another important factor that drives the market is the increased adoption of machine learning and artificial intelligence. Machine learning and AI techniques provide powerful tools for anomaly detection by enabling pattern recognition, statistical modeling, ensemble methods, and continuous learning. These techniques enhance the ability to detect anomalies in complex datasets, improve accuracy, and adapt to changing patterns, making anomaly detection more efficient and effective across various industries and applications. As per Statista, Newsle led the global machine learning industry in 2021 with an 88.71% market share, followed by TensorFlow and Torch. In addition, According to Next Move Strategy Consulting, the artificial intelligence sector increase rapidly over the next decade. Its current worth of roughly USD 100 billion is predicted to more than double by 2030, reaching nearly USD 2 trillion. Also, the growing number of cybersecurity cases and rising adoption of cloud technology would create a lucrative growth prospectus for the market over the forecast period. However, the high cost of Anomaly Detection stifles market growth throughout the forecast period of 2023-2030.
The key regions considered for the Global Anomaly Detection Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the dominance of increased use of smart linked devices, and the Industrial Internet of Things in the region. According to Statista, In 2020, 59% of respondents worldwide rated NetFlow-based analyzers as a very effective tool against distributed denial of service assaults. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as an increase in anomalies as a result of connected devices and the Internet of Things has raised the possibility of a system intrusion in the market space.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.
The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below.
List of tables and figures and dummy in nature, final lists may vary in the final deliverable
List of tables and figures and dummy in nature, final lists may vary in the final deliverable