How to structure my datalake ?

Nowadays I am working on an interesting topic : How to build a datalake. Actually it can be straightforward, this is one possible way to do it :

• Start by creating a directory "datalake" at the root
• Depending on your company / team / project add sub folder to represent your organisation
• Create technical users (for example etl...)
• Use your HDFS security system to configure permission
• Set up quota 
• Add sub-directory for every 
• source
• version of the source
• data type
• version of the data type
• data quality
• partition [Year / Month / Day | Category | Type | Geography]
• Configure workload management for each [technical] users / groups
• For every folder create [once] the metadata to allow users to [many] query it from Hive / HCatalog / Pig / others
• Keep it mind your HDFS block size [nowadays between 128MB and 1GB]
• in order to avoid small file problem
• Use naming standard on the file level to allow data lineage, guarantee one processing 

And so datalake becomes organized and smart raw dump.