Big data, compliance and a highly skilled workforce are driving organizations to transform their current analytical infrastructure to deliver enterprise computing environments that can support the latest in data science and analytics practices. SAS remains a popular choice for statistical programming languages, but there is growing demand for R and Python. Data engineers are now being tasked to deliver scalable and highly available computing resources to support analytics for a growing number of users and increasing data volumes while maintaining security for their customers.
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