Analytics has become an indispensable part of businesses in this data-driven world. With the application it endorses, analytics is being used in every industry/business function, be it sales or marketing analysis or consumer data management. Moreover, its ability to integrate new data collections and build relationships between the new and existing datasets makes it widely popular among professionals. In his article for the ‘Analytics Insight,’ Apoorva Bellapu talks about the importance of Graph Analytics and how it can help build your business.
What Is Graph Analytics?
Graph Analytics can be defined as the relations drawn between business entities, such as customers, products, operations, sales, and others, using graph models to produce information. The generated data is primarily used for search engine optimization and fraud detection but can be used effectively for other purposes too.
Types of Graph Analytics
Graph Analytics is broadly categorized into four categories:
- Path Analysis: Path analysis generally relates the information provided by two nodes. With the path analysis, you can figure out the shortest and widest path to execute a plan.
- Connectivity Analysis: Connectivity analysis measures how strongly connected the nodes are. It helps in determining the weakness and unwanted similarities in the model.
- Community Analysis: It deals with the interaction between the nodes. Community analysis also helps in resolving the behavioral configuration between the nodes.
- Centrality Analysis: Centrality analysis determines the importance of each node.
With data being the most valuable asset globally, it has become crucial for companies to protect it from potential threats. Graph analytics is shaping the industries by preventing fraud detection at a significant scale. In addition, graph analytics has been a helping hand in the utility distribution sector, where it enables the organizations to deliver optimal work in minimum time.
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