Unfortunately, my initial hands-on testing with corrupted datasets reveals a fundamental enterprise problem: impressive capabilities paired with insufficient transparency about data transformations.

In this two-day hands-on session, Johns Hopkins Data Services will cover design concepts of interactive data visualizations and build a Shiny web app from scratch using a prepared dataset.

Interactive visualizations are at the core of the exploratory data analysis process, enabling users to directly manipulate and gain insights from data. In this article, we present three different ways ...

Python is great for data exploration and data analysis and it’s all thanks to the support of amazing libraries like numpy, pandas, matplotlib, and many others. During our data exploration and ...