Data lake or data warehouse first?

I have been confused whether to create a data lake or a data warehouse and hope some experienced real-world professional can give me some enlightenment. I will like to store, visualise and perform machine learning with the data that I ingested from multiple sources (IoT devices, APIs etc.). I read that a business will require *both* data lake and warehouse in the current environment that we are in. My question is: 1. should I create a data lake first, then transform/process these raw data from the lake and ingest it into a data warehouse? 2. Or is the data lake a separate data processing pipeline on its own? 3. Or is this depends on the use case? This has been what I been thinking of: PS: If this is the wrong StackExchange do let me know thanks :)