Tag: workflow
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A compelling family of DSLs for Data Science
[A version of this post appears on the O’Reilly Data blog.] An important reason why pydata tools and Spark appeal to data scientists is that they both cover many data science tasks and workloads (Spark users…
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Reproducing Data Projects
[A version of this post appears on the O’Reilly Strata blog.] As I talk to people and companies building the next generation of tools for data scientists, collaboration and reproducibility keep popping up. Collaboration is baked…
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Data Wrangling gets a fresh look
[A version of this post appears on the O’Reilly Strata blog.] Data analysts have long lamented the amount of time they spend on data wrangling. Rightfully so, as some estimates suggest they spend a majority of…
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Data scientists tackle the analytic lifecycle
[A version of this post appears on the O’Reilly Strata blog.] What happens after data scientists build analytic models? Model deployment, monitoring, and maintenance are topics that haven’t received as much attention in the past, but…
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Simpler workflow tools enable the rapid deployment of models
[A version os this post appears on the O’Reilly Strata blog.] Data science often depends on data pipelines, that involve acquiring, transforming, and loading data. (If you’re fortunate most of the data you need is already…