As the world becomes increasingly data-driven, the need for efficient and effective data analysis tools is more pressing than ever. One area of data analysis that has seen significant growth in recent years is graph analytics, which involves analyzing the relationships between data points in a graph. Graph analytics has a wide range of applications, from social network analysis to fraud detection to supply chain optimization.
However, as the size and complexity of graphs continue to grow, traditional data analysis tools are struggling to keep up. This is where artificial intelligence (AI) and quantum machine learning come in.