Four Big Factors Shaping the Future of Data Science

Inside Big Data  October 26, 2019
As the field grows four trends emerge, shaping data science in the next five years: Accelerate The Full Data Science Life-Cycle – The new concept of data science automation goes beyond machine learning automation, including data preparation, feature engineering, machine learning, and the production of full data science pipelines; Leverage Existing Resources for Democratization – The shortage of data scientists has created a challenge for anyone implementing AI and ML initiatives, forcing a closer look at how to build and leverage data science resources; Augment Insights for Greater Transparency – Increased regulatory oversight like the GDPR has exacerbated the problem. Operationalize Data Science in Business – Data and feature pipelines are much bigger and more complex than ML models themselves, and operationalizing data and feature pipelines is even more complicated. One of the promising approaches is to leverage concepts from continuous deployment through APIs…read more.

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