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We currently have tags for:

difficult to process and manage because the size is usually bigger than the limits software can normally deal with.

A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.

On three questions both tags have been applied.

Are both needed or should one become a synonym of the other?

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    big data is more analytical to say an 18Terrabyte Lidar file. – Mapperz Mar 15 '18 at 20:53
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    With no more than a net 2 vote on any answer there seems little impetus to act on this one at this time. – PolyGeo Mar 29 '18 at 22:43
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Big Data is a recognised technical term and analytical field.

A large dataset is just a large dataset.

I do not think they should be combined, however I believe that if they are combined, should be the master tag.

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While 'big-data' and 'large-datasets' are different things/concepts as mentioned in Midavalo's answer, I think such differences are not reflected in the current way questions are tagged and in GIS SE.

My opinion is that is just being used for expressing 'large-datasets' and doing stuff in software with it. The theoretical part (analytical/science part) is completely missing from those questions.

This is not a surprise given our huge bias toward software/applied questions (for example, we even have a tag when the question is abstract --> Is it useful to have a [gis-principle] tag?).

Moreover, how are we going to draw the line between using one over another and making questions being tagged consistently, so tags become useful for searching both subjects?

Proposal:

Therefore, I vote for synonymizing tags (keep them unmerged for a few months so we can see how it goes) making the master one. A new excerpt could be written to welcome both types of concepts.

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I agree with @Midavalo's answer that:

Big Data is a recognised technical term and analytical field.

A large dataset is just a large dataset.

... and that if they are combined, should be the master tag.

However, I would go further and propose that they are combined by:

  1. Merging the tag into the tag and leaving as a synonym.
  2. For any questions where later ad hoc review suggests that a "large dataset" is not large or complex enough to qualify as Big Data, then the tag should be removed and the largeness of the data involved just be identified by words like "large dataset" in the question body.
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