Surveys of data executives have revealed the top five developing issues in the field of data science and AI, shedding light on the current thoughts and actions of those closely involved in these areas.
Data science is transitioning from an artisanal activity to an industrialized process. Companies are investing in platforms, processes, and methodologies to increase productivity and deployment rates. This shift towards industrialization is aided by automation and the reuse of existing data sets, features, and models. Furthermore, Machine Learning Operations (MLOps) systems are utilised to monitor the accuracy of machine learning models.
