In my last post, I reviewed Five Types of Data Visualizations and broke them down to discovery, quality, storytelling, dashboards/tools and trends/predictive. In this post, I will share some examples of Discovery, Quality, and Dashboard Visualizations. There are too many good examples of Trends/Predicative and Storytelling Dashboards and it was too hard to select one for this post.
Discovery
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| My Network on LinkedIn |
LinkedIn provides this fun tool to help its users visualize and navigate their networks. Data discovery tools have to provide mechanisms to visualize large data sets and help identify relationships. This particular tool leverages color, distance relationships, and zoom in/out to help the user find clusters and potential connections.
Quality
There many tools on the market to help Data Stewards and Data Scientists to identify and address data quality issues. My favorite tools help users identify quality issues and drill down into the data by its dimensions to identify causes and fixes. The tool below is featured in Profiler: Integrated Statistical Analysis and Visualization for Data Quality Assessment
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| Quality issues highlighted in this dashboard |
Dashboards
Tableau Public has numerous examples of interesting visualizations. The one below is a good example of a Dashboard that lets the user see the visualization, review the detailed data, and use filters to drill into results.
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