The only reason to use the log-likelihood instead of the plain old likelihood is mathematical convenience, because it lets you turn multiplication into addition. The plain old likelihood is P(parameters | data), i.e. assuming your data is fixed and you vary the parameters of your model. Maximizing this is one way to do parameter estimation and is known as maximum likelihood.