Dashboards aren’t (quite) dead

Dashboards have evolved from being the primary source for data insights to becoming a complementary tool for large language models (LLMs) in providing consistent, curated views of data. As LLMs gain the ability to analyze data and offer bespoke outputs via simple prompts, the role of dashboards has shifted to ensuring consistency in data representation, which LLMs may lack. Dashboards serve as curated sets of queries that establish agreed-upon metrics for business decision-making, acting as a top-level data curation layer for both humans and LLMs. Despite their reduced centrality, dashboards remain vital for maintaining coherent storytelling from data, especially as they are integrated into workflows for more powerful analyses that combine qualitative and quantitative data. Effective dashboard management involves clear curation to avoid clutter and ensure that key dashboards are authoritative, thereby enhancing their utility as LLM inputs and maintaining coherence across business insights.

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