Data scientists spend a significant amount of time cleaning and munging data, leaving little time for building predictive models in traditional stacks. This is often due to the use of SQL queries that are slow development time and prevent collaboration among team members. The problem persists because data is becoming increasingly social and interconnected, requiring graph databases to store relationships between data points. With the right technology stack, including an open-source NoSQL graph database like Neo4j, data scientists can spend less time writing queries and more time building models, creating a seamless and short development process.