Topic
Data visualization
Data visualization turns measures into patterns a person can compare at a glance. The choice of chart is a choice about which comparison you are making easy, and which one you are making hard.
Chart selection, encoding, readability and uncertainty, for dashboards other people use.
Start hereChart Types: Choose by Purpose, Not by How It LooksMore than forty chart types, grouped by the question they answer rather than by what they look like, with the ones that survive a customer-facing dashboard called out.
Vocabulary
Definitions.
- TermData VisualizationData visualization is the graphical representation of information using visual elements like charts, graphs, and maps to make complex data accessible and understandable.
- TermData AnalyticsData analytics is the process of examining raw data to extract meaningful insights and patterns that drive informed business decisions.
- ArticleData Visualization Best Practices: What Actually WorksWe've seen hundreds of dashboards get built and never used. Here's what separates the ones customers love from the ones they ignore.
Chart selection
Chart types by the question they answer.
- GuideChart Types: Choose by Purpose, Not by How It LooksMore than forty chart types, grouped by the question they answer rather than by what they look like, with the ones that survive a customer-facing dashboard called out.
- ArticleChart Types Guide: Essential and Advanced Charts for DashboardsThe question is not which charts to support but which questions customers need answered. The chart types a customer-facing dashboard actually needs, and the interactions that make them worth embedding.
- ArticleHistogram vs Bar Chart: How to Choose by Data TypeBar charts compare values across categories; histograms summarize a quantitative distribution. Data type, bins, order and area decide which one the question needs.
- ArticleBad Data Visualization: 7 Examples That Kill AdoptionSeven charts that lost their readers, each with the defect named: a truncated axis that turns two percent into a cliff, a rainbow palette assigning meaning the data never had, a third dimension carrying no data at all.
Dashboard design
Layout, colour, interaction, mobile.
- ArticleDashboard Design Principles for Customer DashboardsDesign customer dashboards around decisions, hierarchy, progressive disclosure, consistent semantics, accessibility, and tested user tasks.
- ArticleDashboard Color Theory: How Colors Communicate DataBuild dashboard color roles for grouping, order, status, interaction, contrast, and non-color fallback, then validate them in every shipped state.
- ArticleResponsive Dashboard Design: Beyond Browser ResizingYour customers check analytics on phones during meetings. Here's how to make that experience not terrible.
- ArticleInteractive Dashboard Features: Design a Question LoopFilters, drill-through, refresh, saved views, and actions earn their place when they help a permitted user reach a better decision without losing context.
- ArticleFrom Static Tables to Interactive Analytics: Follow the TaskChoose tables, exports, and interactive analytics from the customer task, then validate demand through observable workarounds and product evidence.
Accessibility and narrative
Accessibility and data storytelling.
- ArticleAccessible Data Visualization: A Release FrameworkTest charts across equivalent content, semantics, operation, visual resilience, runtime states, and real assistive-technology paths.
- ArticleData Storytelling Techniques for Product DashboardsYour customers don't want more data, they want answers. Here's how to turn dashboards into stories that drive decisions.
By product type
Two domain cases.
- ArticleCash Flow Dashboards That Change How You Manage MoneyMost cash flow dashboards show you what happened last month. The best ones help you make decisions about next month.
- ArticleProduction Analytics Visualization: What Manufacturing Customers NeedManufacturing customers now expect interactive production analytics rather than CSV exports. How B2B SaaS companies deliver real-time visibility without a twelve-month build.
- GuideReact Chart Libraries: Compared by Constraint and Use CaseCompare leading React chart libraries using official package evidence, a reproducible benchmark contract, and embedded analytics requirements for production data visualizations in B2B SaaS applications.
By the audience it reports to
The same topic, by industry.
- Sales and CRMPipeline and CRM reporting inside your product
- Operations and Supply ChainOperations and supply chain analytics, with per-number freshness
- FinanceFinance analytics, reconciled to the ledger
- Retail and EcommerceRetail and ecommerce analytics, with comparable store windows
- HealthcareHealthcare analytics, with source reconciliation and access by care relationship
- MarketingMarketing analytics for agencies, white-label per client
- HRHR analytics, scoped by reporting line