How are DS, ML, DL analogous?

Data Science is basically the study of Collecting data, Storing data, Processing data, Describing data ,Modelling data. Modelling of data is done by two types Statistical modelling(we use very simple models for robust statistical analysis & statistical guarantees-it usually works with low dimensional data) and Algorithmic modelling(we deal with complex relationship and build complex models and that’s why we go into the domain of Machine Learning-it can work with high dimensional data),
Machine learning allows you to a large family of very complex functions.
Machine learning estimates the function using the data and by using optimization techniques.
Now, when you have large amount of high dimensional data and you want to learn very complex relationships between the output and domain,
then we use a specific class of complex ML models and algorithms,collectively referred to as Deep Learning.

Nice expelationation