Trend Spotting and Pattern Spotting: Seeing What Matters in Data Visualizations Training in Malta

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.

• 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