Inspiration

To be able to inspect large volumes of data stored in Airtable in an intuitive, fast and performant fashion. Especially relevant when the data is used for Machine Learning workloads.

What it does

Delve into your dataset stored on Airtable and facet/dissect down to the individual record level based on any field therein. It provides an interactive interface for exploring the relationship between data points across all of the different features of a dataset. Each individual item in the visualization represents a data point. Position items by "faceting" or bucketing them in multiple dimensions by their feature values. Success stories of Dive include the detection of classifier failure, identification of systematic errors, evaluating ground truth and potential new signals for ranking.

How I built it

Challenges I ran into

Accomplishments that I'm proud of

What I learned

What's next for Airtable-DataViz-Deepdive

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