| Description |
1 online resource |
| Contents |
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 |
Annotation Machine learning and computerized data analysis is incredibly powerful, but humans still excel at "getting a sense of things"--The ability to recognize ill-defined or novel patterns or anomalies. With the rise of real-time streaming data, it's important to give people access to data as it arrives, in ways that enable users or analysts to recognize that "something is going on." This book provides both conceptual guidance and programming tools to do just that. Streaming data is a fast-moving part of the data field: tools for analysis on streaming and real-time data are at the cutting edge, and visualization of these types of data hasn't caught up. This guide helps close the gap by showing application designers, data scientists, data miners, data journalists, and system administrators several ways to create visualizations that bring context and a sense of time to streaming text data |
| Notes |
Online resource; title from PDF title page (EBSCO, viewed June 11, 2018) |
| Subject |
Streaming technology (Telecommunications)
|
|
Data transmission systems.
|
|
Big data.
|
|
Webcasts as Topic
|
|
BUSINESS & ECONOMICS -- Industries -- Media & Communications.
|
|
TECHNOLOGY & ENGINEERING -- Telecommunications.
|
|
Big data.
|
|
Data transmission systems.
|
|
Streaming technology (Telecommunications)
|
| Form |
Electronic book
|
| ISBN |
9781492031826 |
|
1492031828 |
|
9781492031802 |
|
1492031801 |
|
