The first thing I would consider when comparing data lakes vs data warehouses (https://datalance.net/blog/data-lake-vs-data-warehouse/) would be how your team is using data. A lake can typically store all kinds of data and information raw and unstructured, whereas a warehouse tends to be more designed for structured and cleaned data that is used for reporting and analytics. Lakes are good for data science and exploratory tasks, warehouses are more suitable for BI. Both are not necessarily a superior choice for all organizations. Think of data types, performance of the query, governance, budget and growth before deciding on a choice. Combining both methods sometimes can be a flexible way to get flexibility and reliability in reporting.