Covid and Data Normalization?

Consider the following ‘Common Sense’. I have provided examples of ALL the following in my blogs.

Some people get Covid … don’t die

Some people get Covid … and die

Some people get vaccinated and don’t die

Some people get vaccinated and still die

Some people get vaccinated and still get Covid after being vaccinated

Some people get vaccinated and get very serious side effects (blood clots, aneurysms, paralysis, Covid-Arm, problems with other organs, ‘noisome and grievous sores – blisters – boils.’)

Why are many ‘perfectly healthy’ people dying after getting ANY of the vaccines?

Yes, the vaccine ‘might work’ (or ‘appears to work’) for some and obviously not for others.

98% to 99% percent of People who get ‘Covid’ STILL SURVIVE. THEY DON’T DIE. In other words,

Getting a vaccine is irrelevant for them (and could possibly do them great harm).

If anybody is familiar with the term data normalization will completely understand this due to data redundancy being rampant since this whole thing started the data itself is corrupted and anomolies and even duplicated which they are completely fine with the news doesn't care about anything other then MORE viewers, if you want me to break it down I can do that but don't bring no fake, falsified corrupted data to present your case and talk sensibly.

What is Normalization?

If a database has two or more tables having some same fields it has data redundancy. It causes inconsistency; for example, a customer bought some products from a store, his details are attached to each product wrong, it should have been added only once. We perform normalization to avoid data redundancy. Data redundancy causes data corruption and anomalies in functioning, so it must be avoided when creating a database