Communicating clearly about "samples"
"Sample" as a noun usually refers to a single data point.  "Sample" as a verb is the act of extracting a subset of data points from some larger body (reality or a larger dataset).  The only way to be less ambiguous is use more specific words than "data" or "sample".

Example:

Say you collect 1MM data points from four different sensors in the field giving you four sets of 250k data points.  Say this data is too big for some demo of a model you're testing or an analysis you're running, so you pick 100k data points evenly split across the four sensors (giving four sets of 25k data points).  

In this example, you're sampling twice.  First, to gather your 1MM data points sampling from reality.  Second, you sample again to decrease the size of your data set to something more manageable.  'Data' or 'sample' could refer to reality, the 1MM dataset, the 100k dataset, or any of the sensor-specific subsets.  To make it less ambiguous, establish a unique name as soon as possible for each possible definition you'll be working with.  ('reality' for the set of all possibly observed samples.  'the complete dataset', something derived from the source of the dataset, or even X for the full 1MM dataset.  'our trial dataset', or even Y for the small 100k dataset.

What you actually do comes down to context and what's appropriate for your intended audience, but the general answer is to use more specific words.