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Published : Oct 28, 2020
NOT ON THE CURRENT EDITION
This blip is not on the current edition of the Radar. If it was on one of the last few editions, it is likely that it is still relevant. If the blip is older, it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar. Understand more
Oct 2020
Trial ? Worth pursuing. It is important to understand how to build up this capability. Enterprises should try this technology on a project that can handle the risk.

This edition of the Radar introduces several new tools for creating web applications that help end users visualize and interact with data. These are more than simple visualization libraries such as D3. Instead, they reduce the effort necessary to build standalone analytic applications for manipulating existing data sets. Dash from Plotly is gaining popularity among data scientists for creating richly functional analytics applications in Python. Dash augments Python data libraries much like Shiny sits on top of R. These applications are sometimes referred to as dashboards, but the range of possible functionality is really much greater than the term implies. Dash is particularly suited to building scalable, production-ready applications, unlike Streamlit, another tool in this class. Consider using Dash when you need to present more sophisticated analyses to business users than a low- or no-code solution such as Tableau can provide.

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