Exploring Data: Visualization Training

Exploring Data: Visualization Training

Introduction:

Exploring Data: Visualization Training Course Description

Visualization of data has become a mainstay in everyday life. Whether reading the newspaper or presenting viewgraphs to the board of directors, professionals are expected to be able to interpret and apply basic visualization techniques. Technical workers, engineers and scientists, need to have an even greater understanding of visualization techniques and methods. In general, though, the basic concepts of understanding the purposes of visualization, the building block concepts of visual perception, and the processes and methods for creating good visualizations are not required even in most technical degree programs. This course provides a “Visualization in a Nutshell” overview that provides the building blocks necessary for effective use of visualization.

Exploring Data: Visualization TrainingRelated Courses:

Duration:2 days

Skills Gained:

• Decision support techniques: which type of visualization is appropriate
• Appropriate visualization techniques for the spectrum of data types
• Cross-discipline visualization methods and “tricks”
• Leveraging color in visualizations
• Use of data standards and tools
• Capabilities of visualization tools

Customize It:

With onsite Training, courses can be scheduled on a date that is convenient for you, and because they can be scheduled at your location, you don’t incur travel costs and students won’t be away from home. Onsite classes can also be tailored to meet your needs. You might shorten a 5-day class into a 3-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff’s and site’s requirements.

Course Content:

Overview

Why Visualization?
The Purposes for Visualization: Evaluation, Exploration, Presentation

Basics of Data

Data Elements – Values, Locations, Data Types, Dimensionality
Data Structures – Tables, Arrays, Volumes
Data – Univariate, Bivariate, Multi-variate
Data Relations – Linked Tables
Data Systems
Metadata – Vs. Data, Types, Purpose

Visualization

Purposes – Evaluation, Exploration, Presentation
Editorializing – Decision Support
Basics – Textons, Perceptual Grouping
Visualizing Column Data – Plotting Methods
Visualizing Grids
Images, Aspects of Images, Multi-Spectral Data
Manipulation, Analysis, Resolution, Intepolation
Color – Perception, Models, Computers and Methods
Visualizing Volumes – Transparency, Isosurfaces
Visualizing Relations – Entity-Relations & Graphs
Visualizing Polygons – Wireframes, Rendering, Shading
Visualizing the World – Basic Projections, Global, Local
N-dimensional Data – Perceiving Many Dimensions
Exploration Basics – Linking, Perspective and Interaction
Mixing Methods to Show Relationships
Manipulating Viewpoint – Animation, Brushing, Probes
Highlights for Improving Presentation Visualizations
Color, Grouping, Labeling, Clutter

Tools for Visualization

APIs & Libraries
Development Enviroments
CLI
Graphical
Applications
Which Tool?
User Interfaces

A Survey of Data Tools

Commercial
Shareware & Freeware

Web Browser-based Visualization

Intro –Why Visualize on the Web
Data Driven Documents D3.js: Web Standards: Foundation of D3 (HTML, SVG, CSS, JS, DOM)
Demos and Examples
Code Walk-through
Other Web Tools
Demos and Coding
Walk-throughs

Whether you are looking for general information or have a specific question, we want to help

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Time Frame: 0-3 Months4-12 Months

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