The data I used was created to demonstrate this task in Power BI but there are many real-world network datasets to experiment with provided by Stanford Network Analysis Project. This small dummy dataset represents a co-purchasing network of books.
The data I loaded into Power BI consisted of two separate CSVs. One, Books.csv, consisted of metadata pertaining to the top 40 bestselling books according to Wikipedia and their assigned IDs. The other, Relationship.csv, was an edgelist of the book IDs which is a popular method for storing/ delivering network data. The graph I wanted to create was an undirected, unweighted graph which I wanted to be able to cross-filter accurately. Because of this, I duplicated this edgelist and reversed the columns so the ToNodeId and FromNodeId were swapped. Adding this new edge list onto the end of the original edgelist has created a dataset with can be filtered on both columns later down the line. For directed graphs, this step is unnecessary and can be ignored.
Once loaded into Power BI, I duplicated the Books table to create the following relationship diagram as it isn’t possible to replicate the relationship between FromNodeId to Book ID and ToNodeId to Book ID with only one Books table.
Read on for an example using this data set.