Visual Analytics for Dashboards: A Step-by-Step Guide to Principles and Practical Techniques

This book covers the key principles, best practices, and practical techniques for designing and implementing visually compelling dashboards. It explores the various stages of the dashboard development process, from understanding user needs and defining goals, to selecting appropriate visual encodings, designing effective layouts, and employing interactive elements. It also addresses the critical aspect of data storytelling, examining how narratives and context can be woven into dashboards to deliver impactful insights and engage audiences. Visual Analytics for Dashboards is designed to cater to a wide range of readers, from beginners looking to grasp the fundamentals of visual analytics, to seasoned professionals seeking to enhance their dashboard design skills. For different types of readers, such as a data analyst, BI professional, data scientist, or simply someone interested in data visualization, this book aims to equip them with the knowledge and tools necessary to create impactful dashboards. What you’ll learn The principles of data visualization How to create effective dashboards Meet all the requirements for visual analytics/data visualization/dashboard courses Deepen understanding of data presentation and analysis How to use different kinds of tools for data analysis, such as scorecards and key performance indicators Who This Book Is For Business analysts, data analysts, BI professionals, end-users, executives, developers, as well as students in dashboards, data visualizations, and visual analytics courses. Table of Contents About the Author About the Technical Reviewer Preface Introduction Chapter 1: Dashboards Business Intelligence Objective and Technologies Defining Business Intelligence Business Intelligence Tools Convergence of Disciplines Background Business Dashboard Predecessor Change in User Needs Major Changes Since the 1990s Dashboards Car Dashboard Business Dashboard Definition Objective Key Features Process Supported Dashboard Types Dashboard Classifications Strategic Dashboard Analytical Dashboard Operational Dashboard Dashboard Characteristics Unique Design Common Elements Desired Dashboard Characteristics High-Level Dashboard Product Features Common Dashboard Software Tool Features Drilling Filtering Sorting Pivoting Calculating Charting Dashboard Benefits, Shortcomings, and Challenges Benefits Shortcomings Challenges Obtaining Value from Dashboards Determine the Objective Determine the Expected Value Identify Users Leverage Data Visualization Leverage Advantage over Conventional Reporting Balance Conflicting Display Requirements Selection and Implementation Cost Components Selecting the Dashboard Type What Is the Objective? Which Business Problem Needs to Be Solved? Who Will Use the Dashboard? What Are the Existing Performance Gaps? Identifying the Technical Requirements Implementation Summary Chapter 2: Scorecards Understanding Scorecards What Is a Scorecard Comparing Dashboards and Scorecards Implementing and Using a Scorecard Implementation Issues Metrics Issue Format Issue Standards Issue Collection Issue Use Issue Making an Effective Scorecard Balanced Scorecard Background Objective What a Balanced Scorecard Does Four Balanced Scorecard Perspectives Strategic Areas Financial Perspective Customer Perspective Internal Processes Perspective Learning and Growth Perspective Connection Between Perspectives Comparing Scorecards and Dashboards Three Common Characteristics Applications Layers Types Differences Ensuring Effectiveness Summary Chapter 3: Key Performance Indicators Measuring Performance Why Performance Is Measured Measurement Requirements Linking Measures Metrics Measures and Metrics Difference in Objectives Balancing Metrics How to Obtain the Best Results Key Performance Indicators What Is a Key Performance Indicator? KPI Characteristics KPIs Variety KPIs to Use Benefits and Issues Using and Managing KPIs KPI Management Metrics As Predictors of Success Dashboard KPI Number of Metrics to Include Ownership Metrics Review Data Quality Review Developing KPIs Identifying New KPIs Creating New KPIs Participants in KPI Design and Development Data Requirements Data Collection Methods Identifying the Data Source Data Collection Responsibility Data Collection Frequency Cost Components Temporary Indicators Summary Chapter 4: Dashboard Requirements Objective and Users Objective Users Functional Requirements High-Level User Requirements Basic Requirements Presentation and Display Requirements Output and Distribution Requirements Determining Requirements Objective Questions Metrics Questions Responsibilities and User Action Questions Views/Reports Questions Monitoring Frequency Questions Security Questions Design Questions for User Input User Needs Dashboard Design Placing Data Types of Interactions Summary Chapter 5: Dashboard Design Design Principles Need for Effective Design Features Affecting Dashboard Design Key Design Principles Checklist for Designing Dashboards Impact of Poor Design What Designers Need to Understand Sketches, Mockups, and Prototypes Design for Uniqueness Leveraging External Expertise Architecture How to Architect Dashboards Business and Technical Architecture Effective Principles of Dashboard Design Avoid Information Overload Design for Rapid Monitoring Implement Responsive Design Provide Insight, Not Reports Utilize Valuable Real Estate Avoid Scrolling Use an Iterative Design Process Implement Best Practices and Standards Layout, Colors, and Fonts Layout Chart Elements Colors Visualization Backgrounds Fonts UI Design Principles Importance of UI Design User/UI Interaction Principles of UI Design Structure Principle Simplicity Principle Visibility Principle Feedback Principle Reuse Principle Tolerance Principle Summary Chapter 6: Data Visualization Memory and Cognitive Load Memory Types Iconic Memory Short-Term Memory Long-Term Memory Cognitive Load Need to Visualize Data Memory Limitations Key Characteristics of Good Visualizations Data Visualization in Business Effectiveness of Visuals Comparing Charts with Tables Why Charts Are More Powerful Than Tables Data Visualization for Business Benefits Role in Business Analysis Key to Successful Data Visualization Usage Presentation Media Presentation Media Types Visual Display Elements Used by Dashboards Summary Chapter 7: Visualization Principles Attributes of Visual Perception Pre-attentive Visual Attributes Leveraging Pre-attentive Visual Attributes Four Categories of Pre-attentive Attributes Color Attribute Form Attribute Position Attribute Motion Attribute Gestalt Principles of Visual Perception Gestalt Principles Proximity Principle Similarity Principle Enclosure Principle Closure Principle Continuity Principle Connection Principle Visual Design Considerations Size Color Fonts Chart Scale and Size Chart Scale Chart Size Summary Chapter 8: Visual Communication Visual Cues Placement Position Proximity Lines Shapes Area 3D Shapes and Volume Problem with Circles Impact of Shapes Color Coordinate Systems Cartesian Coordinates Polar Coordinates Geographic Coordinates Measurement Scales Linear and Logarithmic Scales Ratio and Interval Scales Ordinal Scales Nominal Scales Percent Scales Time Scales Visual Context Explicit and Implicit Context Visual Hierarchy Visual Hierarchy Principle Characteristics of Contrast Areas Summary Chapter 9: Understanding and Using Charts Visualizations for Dashboards Variety of Visualizations Plots and Maps Using Charts Tables Chart Types Column Chart Stacked Column Chart Bar Chart Stacked Horizontal Bar Chart Pie Chart Donut Chart Line Chart Bullet Chart Sparkline Chart Treemap Scatterplot Heat Map Funnel Chart Small Multiples Area Chart Bubble Chart Gauges Summary Chapter 10: Selecting Charts Visualization Requirements Purpose What Needs to Be Visualized What Drives the Selection Selecting the Type of Chart to Use Best Fit Finding the Appropriate Chart Mapping Categories Comparisons Proportions Relationships Patterns Summary Chapter 11: Best Practices and Tips Design Provide an Effective Dashboard Design a Single-Screen Dashboard Design the Layout Carefully Position Important Items Strategically Limit Display to What Is Essential Start Design at the High Level Make the Dashboard Communicate Quickly Pick Critical Metrics Enable Interactivity Provide Intuitive Navigation Make It Simple to Access and Use Keep It Current Develop on a Single Platform Information and Its Visual Representation Avoid Mismatch Display Context for the Data Limit Text or Content to Be Displayed Provide Qualitative Data Express Measures Effectively Do Not Make Everything Prominent Presentation Media and Variety Unappealing Visual Display Using an Inappropriate Visual Unnecessary Display Variety Distractions That Hinder Communication Data Issues Excessive Detail or Precision Improper Encoding of Visual Objects Visualization Tips Keep It Visual Leverage Visual Perception Avoid Distracting Visuals Avoid Inappropriate Visual Salience Mute Axis Lines, Borders, and Lines Avoid Grid Lines Use Fill Colors to Delineate Charts Gauges Clutter and Color Mistakes Avoid Screen Clutter Avoid Misusing or Overusing Color Avoid Unnecessary Color Variation Select Colors Carefully Maintain Color Consistency Visuals to Avoid Pie Charts Donut Charts 3D Charts Charts with Secondary Y-Axis Challenges Unique Business Operations Organizational Challenges User Acceptance Data Quality Speedy Implementations Summary Appendix Dissecting the Dashboard Index