In an earlier paper ([8]), an algorithm has been introduced for identifying multivariable linear systems directly from input-output data. This new algorithm falls in the class of so-called subspace methods and resembles impulse response based realization algorithms. In this note, we extend this algorithm by incorporating a balancing step, such that the identified model is always in balanced coordinates. With this modification, one obtains a data driven counterpart for Kung’s realization algorithm.