Data sourcing and cleaning

We have a file of 45000 lines.
Each line is a perfume in the market.
For each perfume there are 3 entries : Brand Name, Perfume Name, Launch Date.
For example : { Channel; Number 5; 1986 }

Our file has many errors (wrong brand names, typos, different spelling for same brand, missing launch date, inversion of brand name and perfume name, concatenation of Brand / Perfume ./ Date in one cell....)

We would need a person or team to check the information in every line and suggest corrections.

For that you will need to go online and look up the information. There are several sources, but none that is a complete exhaustive list, so this is a manual line by line task. It can not be done 100% by use of AI APIs, this will generate many mistakes that will need manual verification anyways.

We are also interested in retrieving a picture for as many fragrances as possible, and having them in a similar format. This can be discussed separately as another job.


Budget is indicative. Prior experience in this type of task a must.



THanks !