> Designing good telemetry is hard, interpreting the data well is harder The biggest problem facing any use of data is quality of the collected data. For examp

> Designing good telemetry is hard, interpreting the data well is harder The biggest problem facing any use of data is quality of the collected data. For example, if you wanted to train a model but all you had were examples of a particular class... well, you excluded yourself from being able to predict any other class from the git-go. Data collection itself require a deep understanding of statistics and probability. Otherwise you’re just shooting yourself in the foot. But let’s be honest, machines don’t “learn” things, people do. Machines have no teleology they determine for themselves. People are both the problem and solution. Anyone who thinks big data and ML will be able to generate the answers are deluded and have already turned off or lost completely their critical thinking skills. Data collection in the form of telemetry is only a mechanism for finding solutions and an incredibly INVASIVE one at that.