Interactive dashboards are BI dashboards that allow users to explore data dynamically rather than viewing static reports. Users can filter, drill down, slice, highlight, and navigate through data to answer their own questions.

Common interactive features include:

• Filters and slicers

• Cross-filtering between visuals

• Drill-down and drill-through

• Tooltips with additional context

• Parameter controls

Interactive dashboards empower self-service analytics. Instead of requesting new reports from analysts, business users can explore data directly within guardrails.

From a BI design perspective, interactive dashboards must balance flexibility with clarity. Too much interactivity can overwhelm users, while too little limits exploration.

Technically, interactive dashboards rely on:

• Well-defined data relationships

• Efficient query engines

• Semantic layers

• Caching and aggregation strategies

Performance is critical. Slow interactions break the experience and discourage usage. This is why interactive dashboards work best when built on optimized data models and pre-aggregated datasets.

Interactive dashboards are widely used across:

• Sales performance analysis

• Marketing attribution

• Product usage analytics

• Operational monitoring

Compared to static reports, interactive dashboards increase engagement, reduce dependency on analysts, and accelerate decision-making. They represent a shift from “report consumption” to “data exploration.”