Understanding data warehouse vs data lake can be confusing because both store business information but serve different purposes. A warehouse is typically organized and normalized data that is ready for reporting and analysis. A lake is more flexible, so that organizations can store information within various formats, such as raw data. The right choice is based on user requirements, workloads, governance needs and analytics objectives. On larger projects, it may be beneficial to discuss architecture with experts like Datalance prior to spending money on a long term system.