In complex data landscapes, understanding and managing relationships between entities is essential for unlocking deeper business insights. Traditional relational models excel at structured data but can struggle with highly interconnected datasets. To address this, SAP Data Warehouse Cloud (SAP DWC) introduces Graph Models — a powerful paradigm for modeling and analyzing relationships between data points using nodes and edges.
This article explores how graph models work in SAP Data Warehouse Cloud, their benefits, and how they help manage complex data relationships effectively.
Graph models represent data as a network of nodes (entities) and edges (relationships). Unlike traditional tabular models, graph models emphasize connections, making them ideal for scenarios where relationships are as important as the data itself.
SAP Data Warehouse Cloud supports graph data modeling and querying through its semantic layer and integrated graph engine. Users can:
Combine customer data with interactions, purchases, social media, and support tickets to gain a holistic view.
Identify suspicious patterns by analyzing relationships between accounts, transactions, and devices.
Map suppliers, manufacturers, warehouses, and shipments to optimize logistics and identify bottlenecks.
Visualize and analyze connections between hardware, software, users, and incidents.
Graph models in SAP Data Warehouse Cloud provide a modern, flexible way to manage and analyze complex data relationships that are difficult to represent in traditional relational structures. By leveraging nodes and edges to map real-world entities and their interactions, organizations can unlock powerful new insights and support advanced analytics scenarios.
Adopting graph modeling expands the analytical capabilities of SAP DWC, making it a versatile platform for next-generation data warehousing and business intelligence.