The author has relaunched their Beergraph, a graphical representation of beer data, with an improved model that utilizes an in-graph index of AlcoholPercentages. This allows for more efficient querying and pathfinding operations, enabling users to find beers with similar characteristics, such as beertype and alcoholpercentage, or beers from the same brewery with similar alcoholpercentage. By "pulling out" the data and normalizing it further, the author has created a more normalized model that facilitates new insights and discoveries, showcasing the potential of graph databases in exploring complex relationships between data entities.