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Streaming Analytics Market Growing at CAGR of 28.2% | Key Players IBM, Oracle, Microsoft, SAP, Software AG

Streaming Analytics Market Growing at CAGR of 28.2% | Key Players IBM, Oracle, Microsoft, SAP, Software AG

IBM (US), Informatica (US), Microsoft (US), SAP (Germany), Software AG (Germany), SAS Institute (US), Oracle (US), Tibco (US), Impetus Technologies (US), Striim (US), WSO2 (US), Inetco (Canada), SQLStream (US), Axonize (Israel), and Espertech (US)

Streaming Analytics Market by Component, Application (Predictive Asset Management, Risk Management, Location Intelligence, Sales and Marketing, Supply Chain Management), Industry Vertical, Deployment Model, and Region – Global Forecast to 2024

MarketsandMarkets expects the global Streaming Analytics Market to grow from USD 10.3 billion in 2019 to USD 35.5 billion by 2024, at a Compound Annual Growth Rate (CAGR) of 28.2% during the forecast period. Streaming analytics is a set of advanced analytical tools that collect, integrate, analyze, and visualize real-time business events and high volume of dynamic live data from various live sources, such as sensors, clickstreams, Radio-Frequency Identification (RFID), Global Positioning System (GPS), social networking sites, and mobile devices, in any data format, to detect and react automatically to urgent business situations in real time. Streaming analytics is about understanding and reacting in a real- time on a particular event in that market space. It helps companies cut inevitable losses, gain operational insights, and grab new opportunities.

The supply chain management segment is expected to grow at the higher CAGR during the forecast period. The supply chain management segment covers big data analytics, a disruptive and essential technology. With growing interest from various supply chain organizations, the demand for streaming analytics is expected to increase in the coming years. Supply chain organizations can improve their response to unpredictable demands and reduce related end-to-end supply chain management issues. Cost-savings in re-structuring supply chains is also one of the important use cases of the streaming analytics technology. With the increasing need for resolving operations-related issues in real-time and the need for streamline operations across industries and vendors, the market will focus on the supply chain management segment to increase their market share.

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The energy and utilities vertical is expected to grow at the highest CAGR during the forecast period. The major vendors of the streaming analytics market plan to deploy smart grids and meters to receive more data about their distribution networks and user behavior and consumption patterns. By storing and processing real-time streams of multi-structured data in a scalable and cost-effective manner, utilities can use next-generation technologies, such as Machine Learning (ML) to optimize their business, thus improving customer experience.

In terms of geographic coverage, the streaming analytics market has been segmented into 5 regions, namely, North America, Asia Pacific (APAC), Europe, Middle East and Africa (MEA), and Latin America. APAC is expected to record the highest growth rate during the forecast period, owing to the growing awareness about real-time analytics solutions among organizations across verticals, which will drive the market in the APAC.

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The major streaming analytics vendors include IBM (US), Oracle (US), Microsoft (US), SAP (Germany), Software AG (Germany), SAS (US), TIBCO (US), Impetus Technologies (US), Striim (US), WSO2 (US), Informatica (US), Kx Systems (US), SQLstream (US), EsperTech (US), and Axonize (Israel). These players have adopted various growth strategies, such as partnerships, agreements, and collaborations; and new product launches, to further expand their presence in the global streaming analytics market. Partnerships and new product launches have been the most dominating strategy adopted by the major players from 2017 to 2019, which has helped them innovate on their offerings and broaden their customer base.

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