Several concerns arise when considering the future of a database, including the potential increase in data volume and the need to adapt to changing business demands. A NoSQL solution, specifically graph databases, is considered due to their flexibility and performance capabilities. However, modeling data as a graph presents challenges, particularly for those accustomed to relational data modeling styles. Graph databases were designed to mimic natural data modeling methods, such as mapping complex data structures on a whiteboard. To effectively model data in this way, it's essential to learn agile coding techniques that can accommodate evolving business and user needs. Fortunately, expert guidance is available through webinars and resources, offering tips and tricks for more effective data modeling, including modeling data incrementally, designing strong queries using Cypher, building a recommendation engine, profiling queries, and determining the need for multiple models.