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Difference between Data lake and Datawarehouse
Data lake and Data warehouse both are used for storing big data.
Data lake is very big storage repository which is used to store raw unstructured data,machine to machine, logs flowing through in real-time. Purpose of the stored data is not defined in the data lake. They are stored for future analysis of the data.
A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose. Dataware collect the data from multiple sources and transform the data using ETL process then load it to the Data Warehouse for business purpose.
| Sr. No. | Key | Data Lake | Data Warehouse |
|---|---|---|---|
| 1 | Basic | Data lake is very big storage repository which is used to store raw unstructured data,machine to machine, logs flowing through in real-time. | A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose |
| 2 | Normalized | Data is not in normalized form | Data warehouse has denormalized schema |
| 3 | Schema Creation | Schema is created after data is loaded | Schema is created before the data is loaded |
| 4 | ELT/ETL | It used ELT process | It used ETL process |
| 5 | Uses | It is ideal for those who want in-depth analysis | It is good for operational users |
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