What prevents people from manipulating data to write better papers? Many papers use nonstandard data sets, which means the authors could have manipulated the data behind the scenes to make their paper look more impressive.  It seems that this could be done very easily: for example, one could cherry pick the items of the data set to make it seem like an algorithm has 90%+ accuracy while in reality it's about 60%.

What prevents people from doing this?  Is there something I'm missing?
Can I use what I described above to publish a paper without much hassle? 


Yes, it's easy to write a fraudulent paper, and it's not hard to get it published if you are willing to publish in a journal with low standards.  (Some predatory publishers will publish literally anything if you are willing to pay them.)  You might even get it published somewhere respectable if you fake everything convincingly, by getting results that are good enough to be impressive without being so implausible that reviewers become suspicious.


  Is there something I am missing?


I'd bet that what you're missing is the role of reputation in academia.  If you don't maintain a good reputation, you'll be ignored and marginalized, with no ability to influence the field.  If your only goal is to produce a paper, then there's a lot of scope for mischief, but this generally won't lead to a successful research career.  If people are unable to build on your work, they'll become suspicious and your reputation will suffer.  (And if they aren't even interested in trying to build on your work, then by definition you aren't having an influential career.)

It's not impossible to succeed in academia by fraud, as demonstrated by the people who succeeded for some years before they were caught.  However, it's much harder than faking a single paper.