This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the RadarUnderstand more
AssessWorth exploring with the goal of understanding how it will affect your enterprise.
Data scientists and engineers often use libraries such as pandas to perform ad hoc data analysis. Although expressive and powerful, these libraries have one critical limitation: they only work on a single CPU and don't provide horizontal scalability for large data sets. Dask, however, includes a lightweight, high-performance scheduler that can scale from a laptop to a cluster of machines. And because it works with NumPy, pandas and Scikit-learn, Dask looks promising for further assessment.