Trend Spotting and Pattern Spotting: Seeing What Matters in Data Visualizations, New Zealand

We can host this training at your preferred location. Contact us!

Data visualization is an important part of analytics. Analytics effectiveness and impact depends on visualization skills of two kinds – ability to create visuals and ability to understand visuals. The real value of visualization does not come from creating visuals, but from understanding what they can tell you. With the language of words we learn reading and writing as separate but related skills. Similarly, with visual language we need to learn understanding (reading) and creating (writing) as distinct but related skills. There are many books, courses, and other resources that teach people how to develop data visualizations but few that teach how to read and understand them. This course aims to fill that gap by teaching the core capabilities of understanding and interpreting data visualizations.

There are no prerequisites for this course.

Business managers, decision makers, analysts and other analytics consumers seeking to refine their skills for understanding data visualizations
Data scientists, data analysts, and other analytics providers seeking to enhance their data visualization skills by understanding visualization from the perspective of the readers
Developers of data visualizations who will improve visualization skills by seeing data visualization through the eyes of the readers

Ten key concepts of data visualization
The most important things to look for when reading visualizations
How to do a “quick read” of data visualizations
How to do a “critical read” of data visualizations
To see trends, patterns, and outliers in visual presentation of data
To see ambiguity, distortion, and bias in visual presentation of data

Part 1: Visual Language

About Language
- Word Languages
- Numeric Languages
- Visual Languages
Visual Language
- Parts, Structure, and Rules
- Visual Communication
- Data Visualization Language
- Interactive Visualization

Part 2: Data Visualization Concepts

Chart and Graph Formats
- Static
- Interactive
- Animated
- Narrated (Storytelling)
Chart and Graph Types
- Basic Types: Line, Column, Bar, Area, Scatter, Bubble, Map, etc.
- Beyond Basics: Tree Maps, Heat Maps, Sunbursts, Clouds, etc.
Patterns and Trends
- Pattern Basics: Center, Spread, Peaks, Mode, Skew, etc.
- Patterns, Trends, and Chart Types
Data
- Data Sets
- Things, Instances, and Variables
- Data Sources and Lineage
Visual Composition
- Axes and Scales
- Legends

Part 3: Quick Reading of Data Visualizations

Finding Context
- First Impression
- Title
- Axes
- Scales
- Legend
Looking at the Data
- Variables and Quantities
- Meaning
- Quick Read Process
- Process Summary
- Quick Read Exercises

Part 4: Critical Reading of Data Visualizations

First Glance
- From a Distance
- Organization
- Visual Appeal
Source of the Chart
- Data Sources
- Data Analyst
- Data Analysis
You and the Chart
- Format and Interaction
- Connections
Reading the Chart
- Title
- Type
- Layout: Aspect Ratio, Legend, Colors, Patterns, Annotation, etc.
- Data: Variables, Encodings, Relationships, etc.
- Axes and Scales: Variables, Coordinates, Units, Intervals, etc.
- Considering Outliers
Finding the Meaning
- Considering Outliers
- Finding Patterns and Trends
- Critical Read Exercises

Upcoming Trainings

Join our public courses in our New Zealand facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

08 November 2024