The dataset comprises bandwidth usage for each customer. There is also a hybrid metric based on the distance covered by each traffic flow and aggregated to obtain 'Bit-Miles' for each customer (sum of traffic $\times$ miles for each flow).
Clearly, there is some (causal) dependence among the above features but owing to skewness I had to resort to transformations (log, square root, z-scores etc.)
After transforming both bandwidth and bit-miles, I see a strong linear relationship.
Does this imply that bit-miles is a redundant feature (which seems counter-intuitive IMHO had there been no transformation)?
Can I somehow prove/disprove that 'Bit-Miles' is redundant?
Here are the plots before and after the transformation.
Here is a small view of the data as well.
Name Traffic(bps) Bit-Miles Customer1 729797243234.54 416983889869721.00 Customer2 411886504711.92 43841920479614.30 Customer3 253240650503.96 269534485841579.00 Customer4 251982742984.49 158900272002478.00