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Graph Analytics Industry By Solutions and Services, Opportunities, Applications and 2027 Forecast Report
Whipsmartmi.com offers "Global Graph Analytics Market 2021-2027" analysis from its research database.Graph Analytics Market is projected to grow up to USD 5,164.72 million by 2027 growing at a CAGR of 33.7% during the forecasting period 2021-2027.
This report offers the major market player’s profiles, such as Oracle, Microsoft, AWS, Neo4j, IBM TigerGraph, DataStax, Franz, TIBCO Software, Cray, Lynx Analytics, Linkurious, Teradata, Graphistry, Dataiku, Tom Sawyer Software, Objectivity, Kineviz, and Expero.
Access to Full Report Summary:https://whipsmartmi.com/Report/Graph-Analytics-Market
The majority of graph analytics vendors provide cloud-based maintenance solutions to maximise revenues and efficiently automate the equipment maintenance process. The use of cloud-based graph analytics solutions is expected to increase as a result of advantages such as simple data maintenance, cost-effectiveness, scalability, and efficient management.
Customer analytics, risk and enforcement management, recommendation engines, path optimization, fraud detection, and other applications make up the graph analytics industry (operations management and asset management). Due to the growing need for finding the fastest and safest route in verticals such as supply chain and logistics, transportation, and retail and eCommerce, the route optimization segment is expected to be the fastest-growing segment in the industry.
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Graph analytics solutions are analytic methods for determining the intensity and direction of connections between objects in a graph. Graph analytics, also known as network analysis, is becoming more common for analytics workloads. For social network influencer analysis, graph analysis is becoming more common. This programme is being used by marketing managers to identify potential targets for marketing campaigns by attempting to build chain reactions within social network audiences to purchase goods and services. It's also used to capture money laundering and other financial crimes. It is also used to detect fraud, such as fraudulent financial transactions and applications, government benefits fraud, insurance applications and claims fraud, and other fraudulent telecommunications activities. These techniques are used to deter violence and conduct counter-terrorism operations.
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