Normalization should be performed in a way that best controls for variability in the experimental protocol from the RNA isolation step through the sequencing runs.
A normalization factor or value is calculated for each sample that should be roughly uniform across the analyzed samples’ datasets. The raw expression values are then divided by the sample-specific normalization factor before continuing with averaging the normalized data and calculating fold change values and p-values.
Various normalization methods exist, and normally you would try a few and choose one that seems to work the best for your dataset. However, with the RNA-seq Analysis Portal and its published and well-established normalization method, you don’t have to worry about these details. It already uses a published and widely-accepted normalization method.