The data science dilemma: Automation, APIs, or custom data science?
As companies place an increasing premium on data science, there is some debate about which approach is best to adopt — and there is no straight up, one-size-fits-all answer. It really depends on your organization’s needs and what you hope to accomplish.
There are three main approaches that have been discussed over the past couple of years; it’s worth taking a look at the merits and limitations of each as well as the human element involved. After all, knowing the capabilities of your team and who you’re attempting to serve with data science influences heavily how to implement it.