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Here's an example of how you could go about this. I've used your sample data.
In this case only one of the email and name pairs generates a match, but you can play around with the fuzzy match options or create additional versions of each name or email to increase this.
Fuzzy matching is more of an art than a science and relies a lot on you coming up with sensible business rules and then structuring your data accordingly. For example, depending on your data, you might want to treat a surname within an email address as a potential match -- in which case you'll need to create additional versions of your records.
The complexity of your workflow can increase dramatically once you start to take into account all the possible variants you want to use for matching (it's common to have more than one fuzzy match tool and then combine the results), but the basic approach is almost always as shown above.