The modern business analyst or data scientist faces challenges both in
increasing data volumes but also an expanding collection of tools for tackling
each problem in the end-to-end data analysis workflow, especially data cleaning
and preparation, analysis, and visualization. Transparency and reproducibility
in data analysis has also become increasingly important for data-driven
decision-making in businesses. Minimizing friction in moving up and down the
data toolchain is critical for delivering effective and timely data
insights. In this talk I’ll examine some archetypal user stories and discuss
technologies and tools that can help improve both individual and organizational
productivity in data workflows.
Innovating analytics and data visualization tools. Author of “Python for Data Analysis” from O’Reilly Media. Author of pandas library, contributor to statsmodels and other Python projects.
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