Many data scientists are working in companies with less advanced technology infrastructure.
But these companies still wish to solve their business problems with the help of data science / analytics.
At this point usually a question arises, “Should we build or buy a solution to solve this problem with data science?”.
As nicely pointed out by this whitepaper from Anaconda, there are a few factors that we should consider before making the decision:
✔️Cost-effectiveness / return on investment
✔️Needs for customisation
✔️Time to value
✔️Vendor dependence
✔️Support required Most data scientists, myself included, have a strong urge to build our own solution to solve a problem.
But is this always the right approach?
Data science solutions – Build vs buy
