Friday, 14 May 2021 01:05 GMT

Streaming Analytics Market Summary, Value Structure Analysis, Growth Opportunities and Forecast To 2027

(MENAFN - Market Research Future) According to Market Research Future (MRFR), the global Streaming Analytics Market is expected to grow at approximately USD 16 Billion at 33% CAGR between 2017 and 2023 (forecast period). The report describes and discusses the effect of the outbreak of COVID-19 on the global streaming analytics market, including potential opportunities and challenges, drivers, and risks.
Streaming analytics, also identified as event stream processing, is the analysis of large pools of current and "in-motion" data by the application of constant queries, called event streams. These streams are triggered by a specific event that occurs as a direct result of an action or a series of actions, such as a financial transaction, a failure of the equipment, a social post or a website click, or some other measurable activity. Data can originate from the Internet of Things (IoT), transactions, mobile devices, cloud applications, web interactions, and machine sensors. By using streaming analytics platforms, organizations can derive business value from data in motion, just as traditional analytics tools will allow them to do with rest data. Real-time streaming analytics benefit a number of industries by detecting opportunities and risks.
Streaming analytics advantages include data visualization, increased competitiveness, elimination of preventable losses, analysis of routine business operations, identifying missed opportunities, generating new opportunities, and many more.

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Competitive Outlook:
The industry giants in the streaming analytics market are Apache Software Foundation (U.S.), Oracle Corporation (U.S.), Microsoft Corporation (U.S.), SAP SE (Germany), Informatica Corporation (U.S.), Software Ag (Germany), Datatorrent (U.S.), Tibco Software (U.S.), Impetus Technologies (U.S.), SQLstream (U.S.) among others.
The global market for streaming analytics has been segmented based on components, application, deployment, organization size, and vertical.
By component, the global streaming analytics market has been segmented into software and service. The service segment involves managed service and professional service. Managed Services can be described as the proactive management of an information technology asset or object by a third party commonly known as an MSP on behalf of the end-user. The operative difference that separates the managed service program is the proactive delivery of their services as opposed to the reactive IT services that have been around for decades. The key factors that contribute to the growth of managed services are the rise in digital information, the need to secure it, a growing trend in bring your own devices, flexibility to meet custom requirements, a constant increase in reliance on heterogeneous networks, and a consistent increase in the complexity of technical solutions.

Regional Analysis:
The regional analysis of the global streaming analytics market is being studied for regions such as the Asia Pacific, Americas, Europe, and the Rest of the World.
The North America region has the largest market share in the streaming analytics market due to the presence of major players in the area, and the adoption of advanced analytics tools by small and large companies is driving the market in the region. Countries such as the United States and Canada contribute a substantial amount of revenue to the streaming analytics market in the region. The Asia Pacific region is expected to rise at the highest CAGR. Enterprises in the region are investing heavily in streaming analytical tools to increase business efficiency and productivity, BI analytics, and various opportunities for diverse industrial verticals to raise the demand in the region.

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Table of Contents:
1 Executive Summary
2 Scope of the Report
2.1 Market Definition
2.2 Scope of the Study
2.2.1 Research objectives
2.2.2 Assumptions & Limitations
2.3 Markets Structure
3 Market Research Methodology
3.1 Research Process
3.2 Secondary Research
3.3 Primary Research
3.4 Forecast Model

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