Despite the data lake being the place where unrefined data is placed, that does not mean it should become a data dump where any sort of data from your company or application ends up and then forgotten.

These are the challenges of a good data lake:

cataloging and discovery (finding the data and classifying data),

moving data (how the data gets to the lake)

storing data

performing generic analytics (making sense of that data),

performing predictive analytics (making educated guesses about the future based on the data).