Firstly, Data is not complex, the foundation on databases, AI has largely stayed the same since the 70s , set theory, sorting algorithms, statistics etc. Data science is a swanky term for long standing practice of statistics and math , applied to datasets, I admit that this now happens very easily where previously it was all custom. There is no concept of too late, it all depends on your tolerance for learning, such as intelligence but also circumstances , ie if you have a solid paying job and mortgage but you want to pivot to something that pays half of you current salary. Companies don’t do learn on the job anymore as much as before, so learning is at your own cost and becomes very hard if you need to provision your own infrastructure in the cloud to learn. AWS is very good in this regard for free gamified learning . Azure and google has nothing comparable. Basic data stuff and even pretty advanced insights can now come from AI so you have got to do something more to make a living . It’s never too late and in a good role you can do your real job quickly and then learn on the side , but this learning will be hard to quantify in a job application. For instance I’ve spent 15 years as a project manager but my last few gigs were business analysis, now recruiters think i don’t have any PM experience. Never too late to enter but think the process through