Build or Buy? Understanding the True Costs of a Data Science Platform
As organizations increasingly strive to become model-driven, they recognize the necessity of a data science platform. According to a recent survey report “Key Factors on the Journey to Become Model-Driven”, 86% of model-driven companies differentiate themselves by using a data science platform. And yet the question of whether to build or buy still remains.
This paper presents a framework to facilitate the decision process, and considers the four-year projection of total costs for both approaches in a sample scenario.
Read this whitepaper to understand three major factors in your decision process:
- Total cost of ownership - Internal build costs often run into the tens of millions
- Opportunity costs - Distraction from your core competency
- Risk factors - Missed deadlines and delayed time to market