Data dashboards

On assuring the client that you are doing something data-sciency because it looks like in the movies

At the intersection of data visualisation and database UI is the data dashboard. AFAICT this means “an exploratory graphing tool for your data which requires little or no programming or statistics special knowledge”. Occasionally useful. Occasionally cargo-culted by bizdev people who don’t know what they are doing. See also, e.g. the open source dashboard framework roundup, or the alternativeto Tableau listing.

Here are some options I am auditioning for some clients.


dash is an open-source dashboard framework for R, Python and Julia. There is an expensive enterprise version also. It is managed by the creators of plotly, the classic web dataviz solution.


A jupyter-specific option.

VoilĂ  turns Jupyter notebooks into standalone web applications.

  • VoilĂ  supports Jupyter interactive widgets, including the roundtrips to the kernel.
  • VoilĂ  does not permit arbitrary code execution by consumers of dashboards.
  • Built upon Jupyter standard protocols and file formats, voilĂ  works with any Jupyter kernel (C++, Python, Julia), making it a language-agnostic dashboarding system.
  • VoilĂ  is extensible. It includes a flexible template system to produce rich application layouts.


Voila-gridstack is a VoilĂ  template started by Bartosz Telenczuk to turn notebooks into dashboards following the specification introduced by the legacy jupyter-dashboards project. The idea behind is to be able to change the layout of the cells to re-configure your dashboards using drag-and-drop. Once you have your desired layout, its configuration stays in the metadata of the notebook. This makes it simple to carry around or share the notebook and its layout configuration.



Turn data scripts into shareable web apps in minutes. All in Python. All for free. No front-end experience required.

Comes with a HTML widget library generating python web apps from code.



Open source software for time series analytics.

From heatmaps to histograms. Graphs to geomaps. Grafana has a plethora of visualization options to help you understand your data, beautifully. […] Bring your data together to get better context. Grafana supports dozens of databases, natively. Mix them together in the same Dashboard.


R can do lots of data analysis, including database analytics as a special case. If you want it to be web-based, shiny can put many queries/regressions/etc online, with all the statistical modelling power of R. This still favours statisticians framing the actual analysis, but given how bad we are at statistics as a species, this might be considered a feature not a bug that it requires you to pass the low-bar of understanding simple statistical software.


Tableau provides commercially-supported dashboard generation. An interesting example of this is the Mapping Police Violence project. It highlights both the insight you can get from this kind of visualisation (Wow they kill a lot of people in the USA) and also the dangerous limitation in these dashboards i.e. straight-up graphs of reported data do not solve difficult statistical modelling problems such as modeling sampling bias, although they might give the impression that this problem is solved. I mean, this is a data tool that come from bizdev people wanting to analyse data collected in-house, which has no sampling error and great control over experiment design, and applying it to the more messy and troublesome data of the noisily-observed real world.



tl;dr autogenerates dashboards based on your database, makes it look like you have been doing something.

Apache Superset is a data exploration and visualization web application.

Superset provides:

  • A wide array of beautiful visualizations to showcase your data.
  • A state of the art SQL editor/IDE exposing a rich metadata browser, and an easy workflow to create visualizations out of any result set.
  • Out of the box support for most SQL-speaking databases
  • [other keywords that only boring bizdev types care about and no one real ever needs]


blazer is a dashboarding/interactive query UI.


  • Multiple data sources - PostgreSQL, MySQL, Redshift, Mongodb…
  • Variables - run the same queries with different values
  • Checks & alerts - get emailed when bad data appears
  • Audits - all queries are tracked
  • Security - works with your authentication system


Metabase. Shanker Sneh, about whom I know nothing, says


  1. Robust and clearly laid out framework. Supports proper database for application metadata.
  2. Feature-rich with easy user, query, segment & dashboard management & classification.
  3. Supports Google SSO, Slack, Email integration.


  1. Framework is Java based. Any customisation will require dev activities from our end.

Database flow

database flow

Database Flow is an open source self-hosted SQL client, GraphQL server, and charting application that works with your database.

Visualize schemas, query plans, charts, and results.

Java app.

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