Complex Event Processing Market size was valued at US$ 3.18 Bn. in 2021 and the total Complex Event Processing revenue is expected to grow by 25.3% from 2022 to 2029, reaching nearly US$ 19.32 Bn.
Complex Event Processing Market Overview:Complex event processing (CEP) is a system that aggregates, processes, and analyses massive streams of data to get real-time insights from events as they happen. Companies nowadays are saturated with data that they are unsure how to apply. CEP separates meaningful data from gibberish by converting low-level data into high-level business insights that enterprises value. CEP enables companies to take control of external events as they occur in real-time. In recent years, Service Oriented Architecture (SOA), Event-Driven Architecture (EDA), cost-cutting in sensor technology, and the monitoring of IT systems owing to legal, contractual, or operational concerns have resulted in a greatly increased occurrence of events in computer systems. This advancement is accompanied by a requirement for these events to be managed and processed in an automated, systematic, and timely manner. The digital revolution has resulted in an increasing need for real-time data analytics, which has raised revenue generation prospects in the CEP sector. Moreover, organizations in the complex event processing market are investing more in industrial automation, which is driving development efforts in machine learning.
Report Scope:The Complex Event Processing market is segmented based on Type, Enterprise, Industry Vertical, and Region. The growth of various segments helps report users in acquiring knowledge of the many growth factors expected to be prevalent throughout the market and develop different strategies to help identify core application areas and the gap in the target market. The report provides an in-depth analysis of the market and contains meaningful insights, facts, historical data, and statistically supported and industry-validated market statistics. It also includes estimates based on an appropriate set of assumptions and methodologies. The bottom-up approach has been used to estimate the market size. Major Key Players in the Complex Event Processing market are identified through secondary research and their market revenues are determined through primary and secondary research. Secondary research included a review of annual and financial reports of leading manufacturers, while primary research included interviews with important opinion leaders and industry experts such as skilled front-line personnel, entrepreneurs, and marketing professionals. Some of the leading key players in the global Complex Event Processing market include IBM Corporation, SAP SE, Oracle Corporation, and Tibco Software Inc. They are continuously strategizing on mergers and acquisitions, strategic alliances, joint ventures, and partnerships for the growth of their market shares. To know about the Research Methodology :- Request Free Sample Report
Complex Event Processing Market Dynamics:
The growing use cases of CEP in industrial applications is a major driver of market growth1. Fraud Prevention and Detection: CEP allows banks to check and identify fraudulent transactions by comparing real-time data to distinct patterns. A new device login can be paired with a password change and other account activities to produce a complicated event that raises the likelihood of fraud. Multiple fraud alarms can be merged to form a higher-level event indicating a system-wide breach. 2. Real-Time Marketing: CEP can be used by e-commerce shops to provide tailored suggestions based on GPS data, social network activity, holidays, and past purchase behavior. One of CEP's primary characteristics is its ability to mix diverse data sources with historical data. 3. Predictive Analytics: Researchers can anticipate the emergence of new coronavirus clusters by integrating events generated by pharmaceutical sales, social networking sites, Twitter, and GPS data. CEP is a natural aspect of the predictive analytics environment since almost all kinds of predictions rely on detecting complicated patterns in huge volumes of data from many sources. 4. Hardware design: CEP was originally developed to help engineers make sense of low-level events occurring in physical hardware in terms of the chip's register-level architecture and instruction set.
The complexities involved in the multimedia data streams CEP is a major challenge for market growthEvery day, billions of photographs and videos are posted and streamed, increasing visual and unstructured data. The unstructured data is extremely expressive to humans, yet they lack descriptive data models and are accessed via sophisticated low-level characteristics. Complex event processing systems are currently confined to processing structured data with a well-defined representation and data model. Multimedia data streams include low-level characteristics, making it challenging for the CEP engine to recognize patterns without a schema or model. Subscriptions are now being provided in a structured format in Event-Based systems so that events may be matched using techniques such as attribute matching. Subscribers must write subscriptions using the event model, which couples him/her to that event model. Multimedia events are extremely difficult to characterize since they may comprise several components with varying connections. As a result, developing an event model for such an occurrence would be impracticable since the user would have to learn a highly sophisticated event framework.
The growing need for real-time monitoring in the IT and services industry is a major opportunity for market growthThe purpose of complex event processing is to recognize and respond to important events (such as opportunities or dangers) in real-time scenarios as rapidly as feasible. These events may occur at different levels of a company as sales leads, orders, or customer support calls. They might also be news articles, text messages, social network posts, stock market feeds, traffic reports, weather forecasts, or other types of data. An event can alternatively be characterized as a "change of state," which occurs when a measurement surpasses a preset time, temperature, or another value threshold. Researchers believe that CEP will provide firms with a new tool to evaluate trends in real-time and will enable the business side to connect more effectively with IT and service divisions. Since then, CEP has been an enabling technology in many systems that take an instantaneous action in response to incoming streams of events. Applications may currently be found in a wide range of industries, including stock trading systems, mobile devices, internet operations, fraud detection, the transportation industry, government intelligence gathering, etc.
Complex Event Processing Market Segment Analysis:By Industry Vertical, the BFSI segment is expected to grow at a CAGR of 9.7% during the forecast period. CEP offers a wide range of applications in the financial sector. A few instances are as follows: 1. High-frequency trading: In general, companies watch market data and trade based on their position concerning the same. High-frequency trading tries to earn a fraction of a penny per share or currency unit on each deal; traders enter and exit short-term positions numerous times each day. Taking up the task of analyzing market data with CEP programs makes the task easier. They not only analyze market data, but they also make trading judgments and exploit trade chances. 2. Smart order routing: Trade orders can be divided or aggregated and placed at several market centers to minimize market impact and obtain the best rates. CEP systems, also known as smart order routers, assist traders in achieving their objectives. SOR collects and caches information from many venues, such as market liquidity, and accepts orders from several sources (OMS, trading systems, ECNs, etc.), splits/aggregates them, and puts orders across multiple venues depending on the cached information and set rules. 3. Risk management: The majority of contemporary risk management software includes post-trade risk analysis. However, CEP traders may perform pre-trade research as well. CEP risk management solutions can sit atop current systems and supplement their capability by simulating executing the transaction against historical data (data for various market situations over time) and providing statistics even before the deal is registered by the trading system. This enables traders to forecast the impact of trade on their portfolios under a variety of market scenarios before engaging in a deal. Risk management is currently the second most popular form of CEP deployment, behind only trading. Banks use CEP-based applications to continually monitor over 50 different types of events. It connects information about transactions that occur in many places and systems within a second or two of each other. The CEP program recognizes patterns of transaction events that suggest the possibility of fraud and either pauses processing or forwards the matter to a person for human adjudication and follow-up. A person creating many new accounts at various branch offices within a few miles of each other is an example of such an event pattern, which may suggest that the customer is setting the scene for fraud. Alternatively, a sequence of credit card transactions, beginning with a few cents and gradually increasing the amounts, to test the credit card processing system's capacity to identify the unwanted entry. Surprisingly, many of the events essential to fraud detection are also relevant to near-real-time cross-selling to legal clients. CEP-based programs regularly analyze significant deposits and withdrawals, as well as address and name changes, to detect life events such as marriage, moving, purchasing a home, or the birth of a child. This real-time event data, together with reference data on the customer's demographics, informs cross-selling suggestions made by tellers, platform bankers, contact center service professionals, and automated Web banking systems.
Complex Event Processing Market Regional Insights:Asia-Pacific is one of the most rapidly growing areas in blockchain technology, accounting for more than 40% of global growth. Digital payments are being driven by digitalization initiatives in emerging nations such as India, and banks are using blockchain technology. As a result, the demand for CEP solutions for effective integration grows. Government efforts and big multi-million dollar technology purchases in the banking sector are driving growth in the Asia-Pacific region. Other reasons, such as the rising need for data storage in small and medium-sized organizations (SMEs) and the proliferation of smartphones, laptops, and tablets in the APAC region, have boosted the region's demand for machine learning applications such as CEP software. Machine learning is being used by retail and consumer products industries in the region to improve customer service and operational efficiency. The Azure cloud, for example, is assisting retail and consumer brands in improving the shopping experience by ensuring that shelves are stocked and items are always accessible when, when, and how the consumer wants to purchase. The BFSI sector in the APAC region is expected to create growth prospects for CEP solutions in the region. Established enterprises and consortia are driving Asian digital banking. Despite structural issues in governance, consortia provide tremendous benefits in terms of size. Tencent-backed WeBank has 200 million clients five years after its establishment, and Alibaba-backed MYbank has more than 20 million SME customers. In a very short amount of time, China's digital banks have amassed an approximately 5% share of the country's RMB 5 trillion ($700 billion) unsecured consumer loan market and more than 7% of online SME loans. KakaoBank, which debuted in South Korea in 2017, drew more than 10 million members in its first year and currently accounts for around 5% of the country's unsecured consumer credit market.
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Complex Event Processing Market Report Coverage Details Base Year: 2021 Forecast Period: 2022-2029 Historical Data: 2017 to 2021 Market Size in 2021: US $ 3.18 Bn. Forecast Period 2022 to 2029 CAGR: 25.3% Market Size in 2029: US $ 19.32 Bn. Segments Covered: by Type • Software • Services by Enterprise • SMEs • Large Enterprises by Industry Vertical • BFSI • Managed Mobility • Government and Defense • Retail • Healthcare • Telecom and IT Industry • Media and Entertainment • Manufacturing • Other
Complex Event Processing Market, by Region• North America • Europe • Asia Pacific • Middle East and Africa • South America
Complex Event Processing Market Key Players• IBM Corporation • SAP SE • Oracle Corporation • Tibco Software Inc. • SAS Institute Inc. • Informatica Corporation • Nastel Technologies Inc. • Software AG • Espertech Inc. • Cisco Systems Inc. • Red Lambda Inc • EMC Inc. • ClearPriority SA • Fujitsu Ltd • Huawei Technologies • Microsoft • Red Hat Inc. • Vitria Technologies • SI Corporation FAQs: 1. Which is the potential market for Complex Event Processing in terms of the region? Ans. APAC is the potential market for Complex Event Processing in terms of region. 2. What are the challenges for new market entrants? Ans. The complexities involved in the multimedia data streams CEP is a major challenge for market growth. 3. What is expected to drive the growth of the Complex Event Processing market in the forecast period? Ans. The growing use cases of CEP in industrial applications is a major driver of market growth. 4. What is the projected market size & growth rate of the Complex Event Processing Market? Ans. Complex Event Processing Market size was valued at US$ 3.18 Bn. in 2021 and the total Complex Event Processing revenue is expected to grow by 25.3% from 2022 to 2029, reaching nearly US$ 19.32 Bn. 5. What segments are covered in the Complex Event Processing Market report? Ans. The segments covered are Type, Enterprise, Industry Vertical, and Region
1. Global Complex Event Processing Market: Research Methodology 2. Global Complex Event Processing Market: Executive Summary 2.1 Market Overview and Definitions 2.1.1. Introduction to Global Complex Event Processing Market 2.2. Summary 2.2.1. Key Findings 2.2.2. Recommendations for Investors 2.2.3. Recommendations for Market Leaders 2.2.4. Recommendations for New Market Entry 3. Global Complex Event Processing Market: Competitive Analysis 3.1 MMR Competition Matrix 3.1.1. Market Structure by region 3.1.2. Competitive Benchmarking of Key Players 3.2 Consolidation in the Market 3.2.1 M&A by region 3.3 Key Developments by Companies 3.4 Market Drivers 3.5 Market Restraints 3.6 Market Opportunities 3.7 Market Challenges 3.8 Market Dynamics 3.9 PORTERS Five Forces Analysis 3.10 PESTLE 3.11 Regulatory Landscape by region • North America • Europe • Asia Pacific • The Middle East and Africa • South America 3.12 COVID-19 Impact 4. Global Complex Event Processing Market Segmentation 4.1 Global Complex Event Processing Market, by Type (2021-2029) • Software • Services 4.2 Global Complex Event Processing Market, by Enterprise (2021-2029) • SMEs • Large Enterprises 4.3 Global Complex Event Processing Market, by Industry Vertical (2021-2029) • BFSI • Managed Mobility • Government and Defense • Retail • Healthcare • Telecom and IT Industry • Media and Entertainment • Manufacturing • Other 5. North America Complex Event Processing Market(2021-2029) 5.1 North America Complex Event Processing Market, by Type (2021-2029) • Software • Services 5.2 North America Complex Event Processing Market, by Enterprise (2021-2029) • SMEs • Large Enterprises 5.3 North America Complex Event Processing Market, by Industry Vertical (2021-2029) • BFSI • Managed Mobility • Government and Defense • Retail • Healthcare • Telecom and IT Industry • Media and Entertainment • Manufacturing • Other 5.4 North America Complex Event Processing Market, by Country (2021-2029) • United States • Canada • Mexico 6. Europe Complex Event Processing Market (2021-2029) 6.1. European Complex Event Processing Market, by Type (2021-2029) 6.2. European Complex Event Processing Market, by Enterprise (2021-2029) 6.3. European Complex Event Processing Market, by Industry Vertical (2021-2029) 6.4. European Complex Event Processing Market, by Country (2021-2029) • UK • France • Germany • Italy • Spain • Sweden • Austria • Rest Of Europe 7. Asia Pacific Complex Event Processing Market (2021-2029) 7.1. Asia Pacific Complex Event Processing Market, by Type (2021-2029) 7.2. Asia Pacific Complex Event Processing Market, by Enterprise (2021-2029) 7.3. Asia Pacific Complex Event Processing Market, by Industry Vertical (2021-2029) 7.4. Asia Pacific Complex Event Processing Market, by Country (2021-2029) • China • India • Japan • South Korea • Australia • ASEAN • Rest Of APAC 8. Middle East and Africa Complex Event Processing Market (2021-2029) 8.1 Middle East and Africa Complex Event Processing Market, by Type (2021-2029) 8.2. Middle East and Africa Complex Event Processing Market, by Enterprise (2021-2029) 8.3. Middle East and Africa Complex Event Processing Market, by Industry Vertical (2021-2029) 8.4. Middle East and Africa Complex Event Processing Market, by Country (2021-2029) • South Africa • GCC • Egypt • Nigeria • Rest Of ME&A 9. South America Complex Event Processing Market (2021-2029) 9.1. South America Complex Event Processing Market, by Type (2021-2029) 9.2. South America Complex Event Processing Market, by Enterprise (2021-2029) 9.3. South America Complex Event Processing Market, by Industry Vertical (2021-2029) 9.4 South America Complex Event Processing Market, by Country (2021-2029) • Brazil • Argentina • Rest Of South America 10. Company Profile: Key players 10.1 IBM Corporation 10.1.1. Company Overview 10.1.2. Financial Overview 10.1.3. Global Presence 10.1.4. Capacity Portfolio 10.1.5. Business Strategy 10.1.6. Recent Developments 10.2 SAP SE 10.3 Oracle Corporation 10.4 Tibco Software Inc. 10.5 SAS Institute Inc. 10.6 Informatica Corporation 10.7 Nastel Technologies Inc. 10.8 Software AG 10.9 Espertech Inc. 10.10 Cisco Systems Inc. 10.11 Red Lambda Inc 10.12 EMC Inc. 10.13 ClearPriority SA 10.14 Fujitsu Ltd 10.15 Huawei Technologies 10.16 Microsoft 10.17 Red Hat Inc. 10.18 Vitria Technologies 10.19 SI Corporation