00:07 We can select the name from backers and do a union and select the name from a set of acquired backers from some other acquired dataset we got. We can order by the name, and now it's not apparent here, but union actually does a distinct on the data.
00:30 If there are duplicates between two different tables, they'll be removed here. We can throw in the ID column just to see what those duplicates are.
00:42 We can see that Brad Pitt is in both tables, Duane Johnson is in both tables, Shamu is in both tables, Pam Beasley.
00:50 We can actually still look up just the names and keep them distinct with union all. If we're interested in getting only these values, but we're interested in getting duplicates of the values for some reason, maybe to prove that they're in both tables, or do run a count over them, then we can do that with union all.