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Tool Category Exploration

Is Mathesar a Database GUI tool?

Based on discussions with the team, the answer is no. While Mathesar shares many of the core features found on database GUI tools, it is not intended to support advanced database administration and operations.

Then what kind of tool is Mathesar?

One of Mathesar’s primary purposes is data storage, with the addition of robust data model customization features, integration with external data sources, data visualization, and sharing capabilities. This combination of features makes Mathesar a mix between a database GUI and analysis & visualization tools.

What might be valuable to Mathesar users?

Most valued features for Data Analysis Tools

Data analysis tools are focused on data manipulation and statistical analysis to aid in decision-making processes. Most commercial tools offer out-of-the-box pre-built data transformations and visualizations to accommodate users of all data-literacy levels.

  • Easily connect to multiple data sources.
  • Create actionable dashboards automatically.
  • Manage data permissions
  • Share data, analysis easily.
  • Automated data transformation (clean and normalize)
  • Team collaboration
  • Formulas, functions, and data modeling
  • Pre-built visualizations
  • Present data in different ways
  • Spreadsheet-like UI

Most valued features for Database GUI Tools

Database GUI tools help database users to manage, manipulate and visualize their data. Compared to the traditional command-line interface methods, GUI tools have a lower learning curve, making it easy to browse databases and tables. One of the top reasons to use a GUI tool is increased productivity reported by the users of such applications.

  • Easy to install
  • Handy administration tools
  • Great user management
  • Secure connections
  • Import and export of standard file types
  • Cross-platform

Most valued features for Visualization Tools

Data visualization tools deal with the graphic representation of data. They are primarily focused on the creation of dashboards and real-time monitoring of data. Performance is essential for these tools as they require running many complex queries to generate the visualizations.

  • Pre-built data connectors
  • Natural language querying
  • Custom infographics
  • Interactive visualizations
  • Guided data discovery
  • Dashboard builder
  • Sharing or embedding outside of the organization (social media, cloud, websites)

Conclusions

  • We don’t want to over-specialize in solving a particular problem as we still haven’t learned enough from target users and how they might apply Mathesar to meet their needs.
  • The roadmap should first focus on the core functionality required to transform various sources of data into normalized databases with minimum effort from users and only then move to the application of those databases into solving more specific problems.
  • We want to make sure that we solve the needs of a single app user before we introduce collaboration features.

Proposed Next Steps

  • Define UX principles based on our current knowledge of potential target users and their needs.
  • Consider how and when we might interact with potential target users during the design process.