Graph Analytics Market Deployment (On-Premises and Cloud), Application (Customer Analytics, Risk & Compliance Management,Recommendation Engines, Route Optimization, Fraud Detection, and Others) OPPORTUNITIES, REGIONAL OVERVIEW, TOP LEADERS, REVENUE AND In

Graph analytics is an analytical tool to determine direction and strength of relationships between objects in a graph. It is focused on pairwise relationship between two objects at structural characteristics. Graph analytics have been helping journalists to navigate through thousands of documents and sources to extract information in a structured format. It is improving logistic services for transportation and manufacturing industries by discovering the safest and fastest routes, and identifying weather conditions. Increase inadoption of graph analytics solution within banks and financial institutions due to the identification of fraud or illegal behavior and criminal acts such as cybercrime and money laundering is contributing toward the growth of the global market. In addition, it helps banks in various activities such as determining sanction loans to an applicant and strengthening institutional or enterprise security.

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The increasing in integration of artificial intelligence and machine learning technology, growing necessity to analyze data in real time, the increasing reliance on the Internet of Things (IoT) has contributed to the growth of the graph analytics market. In addition, the growing demand for analysis of business problem drives the growth of the market. Moreoverdetection of fraud and increasing use of data analytics in digital marketing and technology is driving the growth of the market. However, lack of technical skills related to graph analytics is hindering the growth of the market. Contrarily, the growing need to identify complex patterns and the rapid use of virtualization for big data analytics are expected to provide lucrative opportunities for the market growth.Analytics have become a powerful tool in the finance industry as a means of detecting fraud. The computing power needed for analytics is simplified significantly with graph analytics. Graph analytics excels at establishing patterns between nodes in this case, the categories of nodes are defined as accounts (cardholders), purchase locations, purchase category, transactions, and terminals.

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Graph analytics is applied in many different scenarios such as analyze social networks as they involve a heavy volume of nodes and multi-dimensional connections. Fortunately, graph analytics provides an excellent means for identifying and filtering out bots. For instance, the Oracle team have been using Oracle Marketing Cloud to evaluate social media advertising and traction specifically, and to identify fake bot accounts that skewed data.
Key benefits of the report:

This study presents the analytical depiction of the global graph analytics industry along with the current trends and future estimations to determine the imminent investment pockets.
The report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the global graph analytics market share.
The current market is quantitatively analyzed from 2021 to 2027 to highlight the global graph analytics market growth scenario.
Porter’s five forces analysis illustrates the potency of buyers & suppliers in the market.
The report provides a detailed global market analysis depending on competitive intensity and how the competition will take shape in coming years.

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