Hi Laura,

One code example says more than 1000 words:

gremlin> graph = TinkerFactory.createModern()
==>tinkergraph[vertices:6 edges:6]
gremlin> g=graph.traversal(
traversal(    traversal()   
gremlin> g=graph.traversal()
==>graphtraversalsource[tinkergraph[vertices:6 edges:6], standard]
gremlin> g.addV().property("lang", 45)
==>v[13]
gremlin> g.V().elementMap()
==>[id:1,label:person,name:marko,age:29]
==>[id:2,label:person,name:vadas,age:27]
==>[id:3,label:software,name:lop,lang:java]
==>[id:4,label:person,name:josh,age:32]
==>[id:5,label:software,name:ripple,lang:java]
==>[id:6,label:person,name:peter,age:35]
==>[id:13,label:vertex,lang:45]
gremlin> g.V().values("lang")
==>java
==>java
==>45
gremlin> g.V().values("lang").group().by(map{it->it.get().getClass()}).by(count())
==>[class java.lang.String:2,class java.lang.Integer:1]
gremlin>

So, this query shows you all occurring data types of a specific property in the graph.
Strictly speaking, gremlin OLAP queries are queries using withComputer(). I tend to use the term a bit looser including analytical queries requiring a full table scan.

Best wishes,

Marc