On from Saul Shanabrook's great session introducing the value of tools like Ibis, Altair, Vega and the ibis-vega-transform, we'll dive in a little deeper to see how we can use these tools to explore multiple large datasets with minimal forklifting. Looking at github data again, we'll pull in additional data from disparate sources into an integrated visualization inside JupyterLab to provide more context. We'll show how Ibis provides a seamless analytical API layer across sources, and with particularly fast sources like OmniSci, this opens up a whole world of exploratory analysis.