Not long ago, most data analysis was done using spreadsheets and shared using USB sticks. Although this process was inefficient, analysts were confident that anyone could access and evaluate their work. Although new tools for data wrangling and modeling (e.g. in Python, SQL; also, see above) have emerged, these tools have engendered a sharing gap since notebooks and code may be unapproachable to non-technical users (and can even be a headache for those with programming expertise). In this post, Barry McCardel presents Hex, a solution to the sharing gap which makes it easy to build Python and SQL notebooks, collaborate on them, publish the results as interactive apps, and discover existing and in-progress work.