Keep data, then prepare it for reports
A retailer might put sales records, website activity, and product images in a data lake, often close to their original form. It could then prepare selected sales data for a data warehouse, where people can produce reports such as monthly sales by region.
A data mart is a smaller store of prepared data for one team or subject. A lakehouse combines lake-style storage with tools for organising and analysing data like a warehouse. Services such as BigQuery and Snowflake can provide the warehouse side.
Why teams use both
Many organisations keep original data in a lake and use an ETL process to prepare selected data for a warehouse. Neither guarantees reliable reports: teams still need clear definitions, access rules, and quality checks. If customer details differ between systems, copying them into a warehouse does not decide which is the source of truth.