Data Science needs Machine Learning.
Traditional analytics are adequate for a real-time IoT solution if it’s obvious what you need to measure and what you should do according to the data, but it’s often more complicated than that.
Machine Learning in Data Science
Data models used in traditional data analytics are often static and of limited use in addressing fast-changing and unstructured data. When it comes to IoT, this is a problem if it’s necessary to identify correlations between many sensor inputs and other data feeds which are rapidly producing millions of data points.
While traditional data analysis would need a model built on past data to establish a relationship between data sets, Machine Learning doesn’t; meaning you can use it when you know the answer that you want, but don’t know how to or which is the best way to get to it – it’ll show you the way.