Organizations continue to hone their strategic focus on data-driven decision-making, in turn driving widespread deployment of data science and ML initiatives. However, numerous challenges can prevent the successful integration of data into models and overall organizational strategies and mindsets. The inherent complexity of data science and ML initiatives fuels a rising need for improved agility, efficiency, and performance, along with well-planned risk reduction and compliance measures. Rapidly evolving strategies increasingly reflect a highly diverse data science ecosystem.

To assess the state of data science and ML in today’s organizations, Enterprise Strategy Group surveyed 366 professionals in North America (US and Canada) involved with data science and ML technologies and processes, including potential responsibility for strategizing, evaluating, purchasing, building, and managing these technologies.