Published: 19 April 2022
Traditional analytic approaches struggle to extract important relationships between entities, leaving useful datasets neglected and underleveraged. Data and analytics leaders should use this research to determine when graph analytics are the preferred functionality to address specific use cases.
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Graph analytics are among the most underleveraged capabilities because organizations don’t understand the contrast and complementary nature of graph insights relative to relational analysis.
Complex business problems require exploring and understanding the variable nature of connections and strengths across multiple entities such as organizations, people or transactions.
Organizations wrongly believe graph analytics are limited to niche use cases such as link analysis or social media analysis.
Data and analytics leaders responsible for defining data and analytics strategies should take the following steps:
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