Properly conducted, statistics provide the best analysis of large-number data. Unfortunately, few individuals can perform a rigorous statistical analysis and erroneous conclusions are drawn or at the very least, the data over interpreted.
Case in point, news organizations often present political polling trends of 1 or 2 percentage point drops or increases as if these had any significance. (Most political poles have a margin of error of 3 or 4%.) To report a 1 or 2% change is analogous to tuning a radio a random frequency where no one is broadcasting and turning up the volume, trying to decipher a message from pure white noise.
Thinking about it from a different angle: if set of 100 groups of pollsters, asking the exact same set of questions at exactly the same hour of the day, conducted the same survey, the results would vary by say plus or minus 3.5% That is, there would be at least an 8% difference between the maximum and minimum results for any single question. Moreover, about a third of the 100 surveys would produce answers that are either 3.5% above the average or 3.5% (i.e. 1 standard deviation). It is expected that five surveys would produce that are either 7% above or below the average.
All survey results are equally valid since the exact same survey was given at the same time. The differences in results are simply the inherent random errors of the measurements. The average values from the 100 surveys is likely to be 10 times more accurate than a single one. Thus, the average would still have a 0.35% uncertainty. News organizations are attempting to up their game by taking the averages of perhaps 6 to 9 independent surveys, but those averages are still uncertain by more than 1%, probably more than 2% due to the effects of small number statistics and the mixing of different procedures.
The current discussion has been dealing random errors of repeated measurements. There is often systematic errors in any data. For political polling, systematic errors are injected if there are biases in the questions or if the pollsters fail to sample all demographics correctly.