It would have been a good explanation of normalization had the author picked some better examples for his data. The way it's written, the normalization ends up changing the semantics of the data, which is not what it's supposed to do.
- The normalized schema assumes that the location of a tournament will never change. If the 2014 Australian Open were to be held in Sydney, then looking up the location of the 2012 Australian Open would thereafter yield "Sydney".
- Population has the same problem. It's not likely that the population of a city will remain constant over time. The original database would give you the population at the time the tournament was held. The normalized version always gives you the current population of the city.
I've updated the article to use data that does not (generally) change from year to year: country and area instead of city and population. This should eliminate the semantic issue and make it clearer.
Probably okay for your tutorial...but country areas change from time to time due to territorial disputes being resolved, or due to older erroneous info being changed.
Cities can also change country. Pristina used to be in Serbia but is now in Kosovo (although this is not universally acknowledged). Bratislava used to be in Czechoslovakia but is now in Slovakia.
While just pedantic in this case, it demonstrates how hard it can be to create a strong data model.
Comments
It would have been a good explanation of normalization had the author picked some better examples for his data. The way it's written, the normalization ends up changing the semantics of the data, which is not what it's supposed to do.
- The normalized schema assumes that the location of a tournament will never change. If the 2014 Australian Open were to be held in Sydney, then looking up the location of the 2012 Australian Open would thereafter yield "Sydney".
- Population has the same problem. It's not likely that the population of a city will remain constant over time. The original database would give you the population at the time the tournament was held. The normalized version always gives you the current population of the city.
I've updated the article to use data that does not (generally) change from year to year: country and area instead of city and population. This should eliminate the semantic issue and make it clearer.
Probably okay for your tutorial...but country areas change from time to time due to territorial disputes being resolved, or due to older erroneous info being changed.
Cities can also change country. Pristina used to be in Serbia but is now in Kosovo (although this is not universally acknowledged). Bratislava used to be in Czechoslovakia but is now in Slovakia.
While just pedantic in this case, it demonstrates how hard it can be to create a strong data model.
Yes, that's quite true. Creating even what I would have thought to be a 'simple' example isn't as trivial as I have expected.