Visualization

As explained in Effective Data Analysis

Data visualization is the graphical representation of data to communicate patterns, comparisons, or relationships.

Data visualization represents data graphically so stakeholders can interpret patterns, comparisons, and relationships. Analysts commonly deliver visualizations in reports, presentations, dashboards, and other analytical outputs. section 1.2.4

Choose the form and tool according to the analytical task and stakeholder workflow:

• Static visualizations use charts, graphs, and other visuals in reports or presentations. Spreadsheets, R, and Python can generate them. section 1.2.4
• Dynamic visualizations and dashboards let stakeholders revisit analyses, explore subsets, and answer predictable questions as new data arrives. section 1.2.4
• Tableau and Power BI provide drag-and-drop creation, connections to multiple data sources, and presentation-ready interactive dashboards without requiring programming. section 12.2.1
• Dashboard tools do not replace analysts: they can be weak for long-form exploratory analysis, slow dataset refreshes, and collaboration. section 12.2.1

Figure 12.4 An interactive data-powered app predicting rat sightings, created using Streamlit.

An interactive data-powered app illustrates how visualization can extend beyond reports into reusable stakeholder-facing analytical tools. section 12.2.1

How Effective Data Analysis covers it

How deep it goes

Distinguishes static and dynamic forms, tool choices, workflows, and limitations without detailing visual design principles.

Examples

Uses charts, graphs, reports, presentations, dashboards, Tableau, Power BI, R, Python, and spreadsheets.

What you can do after

Apply via spreadsheets, R, Python, Tableau, or Power BI to create stakeholder-facing visualizations and dashboards.

How it connects

Connects visualizations with dashboards, reports, spreadsheets, programming languages, business intelligence tools, and stakeholder communication.

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  Collaborative Software Design: How to facilitate domain modeling decisionsVisualization is the representation of concepts, relationships, or processes in a visual form to support reasoning and communication.
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  The Well-Grounded Data AnalystData visualization is the graphical representation of data to reveal patterns, comparisons, or trends.
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Compare how 16 books explain visualization →

Related concepts

• bar chartincludes · A bar chart is a visualization that compares quantitative values for discrete categories using rectangular bars whose lengths or heights encode magnitude.
• collaborative discovery and modelingincludes · Collaborative discovery and modeling is a group technique in which stakeholders jointly create and refine representations to establish shared understanding of a domain or system.
• line plotincludes · A line plot is a chart that connects ordered data values with line segments to show changes, relationships, or trends.
• Matplotlibused by · Matplotlib is an open-source Python library for creating static, animated, and interactive data visualizations.
• data explorationused by · Data exploration is the systematic examination and summarization of data to understand its structure, quality, distributions, relationships, patterns, and anomalies.
• Plotlyproduced by · Plotly is a software library and visualization platform for creating interactive, customizable charts and data visualizations.

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.