In the grand scheme of big data things small data is the last mile of data science analysis. It still requires interpretation (or representation) in the form of visualization or application.
Indeed, Wikipedia defines small data but then it goes further by qualifying . I am not certain the latter is true: smaller footprint doesn't automatically qualify data as informative and actionable without more work. In my book small data usually scales to kilobytes and has just a handful of dimensions. But its main feature remains which really means there is simple story behind it.
Case in point could be Google spreadsheet I created this summer while on vacation in Italy. Initially it contained daily miles and steps walked and later I added main attractions for each day. The result was my personal small data covering about 2 weeks of touring Italy with bases in Rome and later in Sicily (this sentence was the story):
As-is this spreadsheet is destined to Google archives contributing to ever growing collection of docs I created and happily forgot about. So I created this visualization that represents both most of data and the story:
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