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Naming Convention

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Naming Convention


we use Dataiku as our primary tool to create data sources for Tableau and any other analytical stuff. I just joined the team and I am finding it difficult to understand the Bigquery target table names. They have everything named as stacked, joined, prepared and the final table sometimes has weird names too.

I would like to have a standard format for namings.  I know dataiku doesn't have any rules but can anyone post any tips on how you guys name your datasets in your org ?

need tips, suggestions any ideas.

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Hi there and welcome to the Dataiku community!

This is just my opinion.. but it is generally good practice to use a dataset naming convention that is both simple in nature but also prescriptive enough for others so that they can quickly get a good idea of what the data or table might contain without spending too much time trying to figure this out. In my experience, names like table_name_stacked, table_name_joined, table_name_prepared, and table_name_final can be fairly common as it tells you what operations or recipe was used previously to produce this dataset/table along with where it belongs in the Flow (table_name_final likely being the final output of the data transformation, cleansing, preparation, wrangling, etc. that was done and should thus be used as the input for your BI tool/layer). 

However, this is merely one perspective and can indeed differ quite greatly based on the individual's or organization's preferences and needs/requirements. 



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