  We show through intensive simulations that the paradigmatic features of
anomalous diffusion are indeed the features of a (continuous-time) random walk
driven by two different Markovian hopping-trap mechanisms. If $p \in (0,1/2)$
and $1-p$ are the probabilities of occurrence of each Markovian mechanism, then
the anomalousness parameter $\beta \in (0,1)$ results to be $\beta \simeq 1 -
1/\{1 + \log[(1-p)/p]\}$. Ensemble and single-particle observables of this
model have been studied and they match the main characteristics of anomalous
diffusion as they are typically measured in living systems. In particular, the
celebrated transition of the walker's distribution from exponential to
stretched-exponential and finally to Gaussian distribution is displayed by
including also the Brownian yet non-Gaussian interval.
