Visualizing Streaming Data
Interactive Analysis Beyond Static Limits
Paperback Engels 2018 1e druk 9781492031857Samenvatting
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.
- Determine your company's goals for visualizing streaming data
- Identify key data sources and learn how to stream them
- Learn practical methods for processing streaming data
- Build a client application for interacting with events, logs, and records
- Explore common components for visualizing streaming data
- Consider analysis concepts for developing your visualization
- Define the dashboard's layout, flow direction, and component movement
- Improve visualization quality and productivity through collaboration
- Explore use cases including security, IoT devices, and application data
Specificaties
Lezersrecensies
Inhoudsopgave
Who This Book Will Benefit
How This Book Is Organized
Conventions Used in This Book
Using Code Examples
O’Reilly Safari
How to Contact Us
Acknowledgments
1. Introduction
Why Visualizations
The Standard
Terms
Data Formats
Data Visualization Applications
Assumptions and Setup
2. Goals
Presentation Goals
Pre-batch Analysis
The Analyst Decision Queue
Data Pipeline Visualization
Show Movement on a Map
Asking New Questions
Seeing Frequency and Order
3. Data Sources
Data Source Types
What to Stream
Data Storage Considerations
Managing Multiple Sources
4. Streaming Your Data
How to Stream Data
Buffering
Streaming Best Practices
5. Processing Streaming Data for Visualization
Batch Processing
Inline Processing
Processing Patterns
Lookups
Lookup Types
Normalizing Events
Extracting Value
The JSON Collection Decorator
Processing Checklist
Streaming Statistics
Types of Statistics
Record Context Checklist
Scaling Data Streams
Presenting Processing
6. Developing a Client
Native or Browser Development
Frameworks and Libraries
A Common Approach
Getting Started with the Sample Client Application
Client Libraries
Code Structure
Alternative Approaches
Showing Streaming Data
Events
Logs
Records
Dashboards
Visual Elements and Properties
Data Density
Dividing Time
Time to Live
Context
Visual Language
Appropriate Displays
8. Visualization Components
Records
Statistics
Visualizations
Streaming Options for Common Visualizations
Streaming Visualization Techniques
Bar Chart Example
Static Information
9. Streaming Analysis
Visual Distractions
Visual Deception
Cognitive Bias
Analysis Models
Visual Analysis
Streaming Analysis Workflow
Context Awareness
Outliers Example
10. Workflow Visualization
Updating Processing
Interacting with Visualizations
Storing Decisions
11. Streaming Data Dashboard
Layout
Flow Direction
Component Movement
Autopilot
12. Machine Learning
Machine Learning Primer
Machine Learning and Streaming Data Visualization
Presenting Machine Learning Results
Supervised Learning and Continuous Tuning
Presenting the Unexpected
Machine Learning Decisions on What to Display
13. Collaboration
Why Collaborate
Sharing Out
14. Exports
Configurations
Datasets
Streaming Replay Reports
Static Reports
Submitting Processing Updates for the Data Feed
15. Use Cases
Security
Machine Learning Interaction
Smart Devices (aka the Internet of Things)
Brand Monitoring
Public Opinion
Application Data
Error Monitoring
Collaboration
Workflow
Analyst Input
Data Exploration
Examples
Powerboard
Vizceral
Alooma Live
Stream-Viz
16. Summary and References
Links Mentioned
Data
Transform and Filter
Presentation Dashboards and Components
Interactions and Actions
Beyond the System
Index
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