Summary
In this chapter, we have seen how we can map the data to graph model using Arrows.app (https://arrows.app/#/local/id=jAGBmsu828g36qjzMAG4), along with working with the browser to load the data using LOAD CSV commands. Along the way, we looked at when to make a value a property or a node or use it an extra label that makes understanding our data much easier in a graph format.
We also discussed various commands for conditional data loading, such as using FOREACH to simulate an IF condition. We also looked at conditional data loading by combining a WHERE clause with a WITH clause.
Along the way, we discussed how the graph data model evolves as we keep considering more data being added to the database. This is made possible since Neo4j is a schemaless database. In a schema-strict database such as an RDBMS, we have to think through all the aspects of the data model before we can attempt to ingest the data. This makes data modeling iterations simpler and gives us the opportunity...
