A data-inventory workshop drops SMS complaints, transit-app clicks, and SCADA heartbeats into one unlabeled ‘sensor’ bucket. What correction should facilitators make?
Select an answer to reveal the explanation.
Short Explanation
Three very different animals got tossed in one kennel labeled ‘sensor.’ Texts are people-to-people, taps are people-to-apps, and SCADA pulses are machines-to-machines. Split the kennel or the architecture will bite later.
Full Explanation
Accurate source typology separates person–person, person–machine, and machine–machine classes. SMS complaints, app clickstreams, and SCADA heartbeats exemplify those three classes respectively. Collapsing them into a vague ‘sensor’ label hides Velocity, privacy, and pipeline differences. Facilitators should reclassify before tool selection.