Quansight's data visualization experts can create automated workflows that allow your organization share and explore data based on the insights discovered by your data science team.


Well designed visualizations can communicate valuable insights in the data. Interactive visualizations and dashboards go a step further, connecting different views of complex data and allowing an exploration of cause and effect that builds a greater intuition.

Creating, maintaining, and sharing these kinds of visualizations can be challenging. Typically an engineer or data scientist explores the data using many analyses and visualizations that are often thrown away after key insights are found. Summary visualizations or static reports are used to communicate these results to others. If the visualization is particularly useful, it is thrown over the wall to a separate team of JavaScript developers, who recreate the visualization in a form that can be published via the web. The result is often a beautiful interactive visualization.


The challenge with this approach is the disconnect between the subject matter experts and the end visualizations. Sharing becomes an expensive and time consuming proposition. Early insights are often lost in translation and customization of the visual message for multiple audiences is a significant effort. And each time a data scientist comes up with a new way of looking at the data, the JavaScript developer does the work again to prepare the visualization for publication.


We can build - or show you how to build - an integrated visualization workflow that converts the analysis into a published dashboard with multiple linked interactive visualizations that can be automatically updated and quickly modified. We bridge the gap between the worlds of the data scientist working in Python and Jupyter with that of the web publishing.

These visualizations can be used by non-technical staff to better understand the data. Technical staff can easily make changes to the visualizations. And data scientists can modify the underlying analyses to reveal new insights.


1. Using Jupyter Lab and Notebooks we create an integrated workflow to access and analyze your data.


2. We then use the latest in visualization tools like Holoviews, Matplotlib, Plotly, Datashader and Bokeh to create impactful images of your data.


3. Finally, we use Panel to create multi-image dashboards and publish them to the web. The result is a power dashboard of visualizations for your organization that is sharable, repeatable, and maintainable. Connect with us about improving your visualizations today.

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