Sliding mode control (SMC) is a robust control strategy that is effective against disturbances, delays and model uncertainties; but similar to other control strategies, SMC is a model-based control method, and the complexity of certain industrial processes makes model estimation a highly difficult task. Furthermore, the growing interest on Industry 4.0 and the new requirements for control loops raise some questions about the future role of this controller in the industrial field. In this work a design methodology for sliding mode control based on data-driven control concepts is presented. Beginning with an extended-state Kalman filter for unknown output estimation, with this information the discrete-time reachability law is derived for the calculation of the control law. Finally, the proposal is evaluated in a simulated mixing plant and implemented on the TCLAB process.