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Complex Event Processing Market: Segmented: By Application (BSFI, Dynamic Pre-Trae Analytics, Fraud Detection, Government and Defense, Healthcare and Others), By Deployment (Cloud-based and On-Premise), By service Type (Consulting, Installation and Maintenance, Training and Support and Managed Services), And Region - Global Analysis of Market Size, Share & Trends For 2019-2020 And Forecasts To 2031
[ 170 + Pages Research Report ] Complex Event Processing Market to surpass USD 72 billion by 2031 from USD 5.3 billion in 2021 at a CAGR of 29.9% in the coming years, i.e., 2021-31.
Complex event processing also referred to as event, stream, or event stream processing is the use of technology to query data before it is recorded in a database or, in some situations, before it is ever stored. Complex event processing is a real-time organizational tool that helps to collect a large amount of data and identify and evaluate cause-and-effect links between occurrences. CEP analyses continually arriving inputs to a pattern & reports on what's going on. It also enables you to take proactive, effective steps. CEP, according to analysts, will provide enterprises with a new approach to evaluating patterns in real-time and enable the company to connect more effectively with IT & service departments. Many systems that take instantaneous action as a result of an incoming stream of events now use CEP as an enabling technology.
The global Complex Event Processing market is expected to project a notable CAGR of 29.9% in 2031.
As the no. of sensors and linked devices grows, so does the amount of data being saved. The problem of evaluating this data in real-time is a challenge in the Database Management System method. Complex Event Processing (CEP) is a solution to this problem since it works on the stored query instead of the stored data.
BFSI segment to grow with the highest CAGR during 2021-31
The increasing adoption of technologies such as blockchain & Big Data analytics in the field is leading to the use of CEP systems to make real-time decisions. Banks and trade firms are heavily investing in the blockchain, which has led to the adoption of CEP systems. CEP systems aid in the integration of the digital transaction lifecycle across multiple business entities, consumers, systems, and technology. With CEP, the event handler must be set up to listen for a change in the blockchain or associated endpoints, then correlate and activate suitable CEP rules to generate an action or alert.
A cloud-based segment to grow with the highest CAGR during 2021-31
Due to many advantages like as cheap operational expenditure, easy implementation, scalability, and easy cooperation, large companies or small and medium enterprises are exhibiting a strong interest in cloud-based CEP systems. Furthermore, as the mobile workforce, as well as the number of smartphone users, grows, leading firms strive to provide convenient and easy-to-use applications. Companies' continuing internationalization and the rise in content among businesses have prompted them to facilitate the aggregation of business-critical material through a single point supplied by CEP solutions. Similarly, as the complexity of storing and managing this data grows, more organizations are adopting cloud-based deployments as a means of providing a centralized database for their master data.
Increasing use of complex event processing for security purposes
The CEP market is predicted to grow due to unprecedented market risk, security threats, and the demand for simpler & consumer-oriented analytical software. The growing requirement for management & analytical capabilities for large amounts of data arising from operations is driving the use of Complex event processing (CEP) technology in a variety of industries. Traditional data analysis software takes a long time to process, and its response time to a potential company danger is slow. Demand for technologies like CEP, which can deliver rapid or real-time identification and reaction, is increasing.
Rising need for CEP in organizations
The increasing complexity of vital data management has compelled enterprises to use CEP as the primary custodian for their master data. In enterprises, a large number of data is collected, which may include customer relation management, transaction processing system, procurement analytics, or any other enterprise-grade system, making CEP an indispensable tool. For most businesses, data collecting, combination, and analytics technologies are necessary for storing and securing data.
CEP extracts patterns from data streams & sends timely notifications to users
Complex Event Processing (CEP) extracts patterns from data streams & sends timely notifications to users. Due to their unstructured data type and shortage of expressive query language, current CEP technologies have inherent disadvantages when it comes to querying video streams. However, the CEP market's expansion is being stifled by a patchwork of government laws and policies that span domestic and international borders.
Company Overview, Business Strategy, Key Product Offerings, Financial Performance, Key Performance Indicators, Risk Analysis, Recent Development, Regional Presence, SWOT Analysis
The global Complex Event Processing market is segmented based on regional analysis into five major regions: North America, Latin America, Europe, Asia Pacific, and the Middle East and Africa. Asia-Pacific is among the most rapidly developing areas on the planet. Government initiatives and huge multibillion-dollar technology agreements in the banking sector are driving growth in Asia-Pacific. Other factors, such as the growing need for data storage among SMEs and the growing prevalence of smartphones, laptops, & tablets in the APAC area, have boosted the demand for applications of machine learning in the region.
COVID-19 is a worldwide pandemic that has damaged work, social life, and also the economy in over 185 nations. Keeping track of people's virus-spreading risk behavior can assist to keep the number of COVID-19 cases from rising. Radiofrequency technology was employed in recent research to capture human movements and identify coughing in a room. Modeling this behavior using complicated events could be one way. Objects are automatically recognized & tracked using smart camera and DL algorithms to create these events from simple occurrences. A complicated event detection algorithm is then used to detect complex events.
Global Complex Event Processing is further segmented by region into:
Complex Event Processing Segments:
| Report Attribute | Details |
| The market size value in 2021 | USD 5.3 billion |
| The revenue forecast in 2031 | USD 72 billion |
| Growth Rate | CAGR of 29.9% from 2021 to 2031 |
| The base year for estimation | 2020 |
| Quantitative units | Revenue in USD billion and CAGR from 2021 to 2031 |
| Report coverage | Revenue forecast, company ranking, competitive landscape, growth factors, and trends |
| Segments covered | Deployment, Service Type, Application, and Region |
| Regional scope | North America, Europe, Asia Pacific, Latin America, Middle East & Africa (MEA) |
| Key companies profiled | Nastel Technologies, Informatica, Software Ag, Espertech Inc., Oracle Corporation, IBM Corporation, Sas Institute, Red Hat, Tibco Software, Sap Se, Wso2 Inc., and Other Prominent Players. |
The Complex Event Processing Market size was estimated at USD 5.3 billion in 2021 and is expected to reach USD 72 billion in 2031.
Key players: Nastel Technologies, Informatica, Software Ag, Espertech Inc., Oracle Corporation, IBM Corporation, Sas Institute, Red Hat, Tibco Software, Sap Se, Wso2 Inc
BFSI segment & A cloud-based segment are anticipated to hold the largest Complex Event Processing Market.
Increasing use of complex event processing for security purposes and Rising need for CEP in organizations
Complex event processing also referred to as event, stream, or event stream processing is the use of technology to query data before it is recorded in a database or, in some situations, before it is ever stored. Complex event processing is a real-time organizational tool that helps to collect a large amount of data and identify and evaluate cause-and-effect links between occurrences.
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