If all you are trying to do is create another dataset that has a similar distribution to your existing dataset with similar covariances, variances, etc. then you could simply draw a single bootstrap sample, by sampling with replacement from your original dataset.

Here's a quick example in R. Say your data looks like the data in mydata.

#Generate some fake data for demonstration
logins<-rpois(1000, lambda=2)
revenue<-rnorm(1000, 500, 20000)
mydata<-data.frame(logins, revenue)

#examine distributions of the data with historgrams
hist(mydata$logins)
hist(mydata$revenue)

#Draw 1000 samples with replacement from the existing dataset
simulated.data<-mydata[sample(NROW(mydata), size=1000, replace = TRUE),]

#Verify that the resulting distribution looks similar to the original
hist(simulated.data$logins)
hist(simulated.data$revenue)

When you do this, you'll see that the distributions of both the original data and simulated data look very similar. But I suspect you are trying to do something more complex with your analysis. If you can tell us what you are trying to do, I can update this answer with better guidance.