At a CAGR of 20.3% | Graph Analytics Market Emerging Trends, Top Leading Players with Strategies 2031

The increasing integration of artificial intelligence and machine learning technology, the growing necessity to analyze data in real-time, and the increasing reliance on the Internet of Things (IoT) have contributed to the growth of the graph analytics market. In addition, the growing demand for analysis of business problems drives the growth of the market.

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Moreover, the detection of fraud and the 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.

The top major companies covered in this market include Amazon Web Services, DataStax Inc., International Business Machines Corporation, Lynx Analytics, Microsoft Corporation, Neo4j, Oracle Corporation, Teradata Corporation, and TigerGraph Inc.

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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 the coming years.

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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.

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.

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Impact of COVID-19 on Graph Analytics Market:

• The global impacts of the coronavirus disease 2019 (COVID-19) are expected to significantly affect the graph analytics market in 2020.

• Lockdown and travel restrictions across the globe have led to a reduction in demand for entertainment product drastically, which impacts the e-commerce industry in a negative manner and hampers growth of the market.

• However, it is expected that post the pandemic, with no travel restrictions and businesses coming back on track, the demand to gain insights on consumer behavior would subsequently increase and, in turn, boost the growth of graph analytics market.

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