📌 Graph-Based Analytics Summary
Graph-based analytics is a way of analysing data by representing it as a network of connected points, called nodes, and relationships, called edges. This approach helps to reveal patterns and connections that might be hard to spot with traditional tables or lists. It is especially useful for understanding complex relationships, such as social networks, supply chains, or web links.
🙋🏻♂️ Explain Graph-Based Analytics Simply
Imagine you have a big group of friends and you draw lines between everyone who knows each other. Analysing this drawing helps you see who is the most connected or who acts as a bridge between different groups. Graph-based analytics is like using these drawings to answer questions about connections and influence.
📅 How Can it be used?
Graph-based analytics can help identify influential users in a social media network for targeted marketing.
🗺️ Real World Examples
A bank uses graph-based analytics to detect fraud by mapping transactions between accounts as a network. By analysing the connections, they can spot unusual patterns, such as a group of accounts sending money in circles, which might indicate money laundering.
A logistics company applies graph-based analytics to optimise delivery routes by representing warehouses and delivery points as nodes and roads as edges. This helps them find the most efficient paths and reduce delivery times.
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