Introduction -- Goals -- Data sources -- Streaming your data -- Processing streaming data for visualization -- Developing a client -- Presenting streaming data -- Visualization components -- Streaming analysis -- Workflow visualization -- Streaming data dashboard -- Machine learning -- Collaboration -- Exports -- Use cases -- Summary and references.
Summary:
While tools for analyzing streaming and real-time data are gaining adoption, the ability to visualize these data types has yet to catch up. Dashboards are good at conveying daily or weekly data trends at a glance, though capturing snapshots when data is transforming from moment to moment is more difficult--but not impossible. With this practical guide, application designers, data scientists, and system administrators will explore ways to create visualizations that bring context and a sense of time to streaming text data. Author Anthony Aragues guides you through the concepts and tools you need to build visualizations for analyzing data as it arrives.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.