- Duration: 3 days
- Skill-level: Foundation-level Visualizing Graph Data for Intermediate skilled team members. This is not a basic class.
- Targeted Audience: This course is geared for those who wants to turn their rich data into important insight? Complex relationships in large data sets can be difficult to recognize. Visualizing these connections as graphs makes it possible to see the patterns, so you can find meaning in an otherwise over-whelming sea of facts.
- Hands-on Learning: This course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises. Student machines are required.
- Delivery Format: This course is available for onsite private classroom presentation, or remote instructor led delivery, or CBT/WBT (by request).
- Customizable: This course may be tailored to target your specific training skills objectives, tools of choice and learning goals.
Visualizing Graph Data teaches you how to understand graph data, build graph data structures, and create meaningful visualizations. This engaging course gently introduces graph data visualization through fascinating examples and compelling case studies. You’ll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data. By the end, you’ll have a conceptual foundation as well as the practical skills to explore your own data with confidence
Working in a hands-on learning environment, led by our Visualizing Graph Data instructor, students will learn about and explore:
- Visualizing Graph Data teaches you not only how to build graph data structures, but also how to create your own dynamic and interactive visualizations using a variety of tools.
- You’ll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data
- This course is loaded with fascinating examples and case studies to show you the real-world value of graph visualizations.
- You’ll have a conceptual foundation as well as the practical skills to explore your own data with confidence
Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below
- How to understand graph data structures, and create meaningful visualizations
- Techniques for creating effective visualizations
- Examples using the Gephi and Key Lines visualization packages
- Real-world case studies
Audience & Pre-Requisites
This course is geared for those who wants a conceptual foundation as well as the practical skills to explore your own data with confidence.
Pre-Requisites: Students should have
- No prior experience with graph data is required.
- Good foundational mathematics or logic skills
- Basic Linux skills, including familiarity with command-line options such as ls, cd, cp, and su
Course Agenda / Topics
Part 1. Graph visualization basics
- Getting to know graph visualization free
- Getting to know graphs
- Getting to know graph visualization
- Case studies
- Intelligence and terrorism
- Credit card fraud
- Cyber security
- Sales and marketing graphs
- An introduction to Gephi and Key Lines
Part 2. Visualize your own data
- Data modeling
- What is a data model?
- Graph data models
- Graph databases
- How to build graph visualizations
- Understanding your user
- Using intuitive visual properties
- Building charts with visual properties
- Creating interactive visualizations
- Chart navigation
- Declutter your charts
- Data volumes
- Animations and mobile
- How to organize a chart
- Force-directed layouts
- Other layout options
- Big data: using graphs when there is too much data
- Controlling which nodes and edges are visible
- Grouping and combinations
- Dynamic graphs: how to show data over time free
- How do graphs change over time?
- How to visualize changes over time
- Implementing dynamic graphs
- Graphs on maps: the where of graph visualization
- Working with geographical data
- Overlaying graphs on maps
- Building graphs on maps