
Introducing Basedash Skills
Skills are reusable bundles of instructions that every Basedash AI surface — chat, charts, dashboards, automations, insights, and tasks — can read on demand. Teach Basedash once, and it learns everywhere.

Skills are reusable bundles of instructions that every Basedash AI surface — chat, charts, dashboards, automations, insights, and tasks — can read on demand. Teach Basedash once, and it learns everywhere.

A practical playbook for diagnosing and fixing slow BI dashboards: SQL, warehouse tuning, caching, dashboard design, and tool-specific tips.

A practical framework for managing BI dashboard sprawl: a four-tier trust model, a 60-minute audit, retirement rules, and an ownership model that lasts.

How operational and analytical dashboards differ in audience, refresh rate, and layout, with a design checklist for each and when one tool can do both.
“Nous avons évalué Omni et d'autres outils BI, mais la rapidité pour obtenir un insight avec Basedash est inégalée.”
Greg Demoge
Co-fondateur et CPO · FullEnrich
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“Pour une entreprise aussi soucieuse de sécurité que la nôtre, Basedash a immédiatement fait tilt. Des rapports qui prenaient des semaines sont prêts en quelques heures.”
Claudio Godoy
AI Agents Lead · Taxfyle
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A practical guide to choosing how often your BI dashboards should refresh: live queries vs scheduled extracts vs cached snapshots, with tradeoffs for cost, freshness, and performance.

Compare 7 financial reporting platforms in 2026 for close automation, board packs, statutory filing, and FP&A reporting (Workiva, Vena, OneStream, and more).

Today we're launching MCP connectors — plug Linear, HubSpot, Slack, Resend, Notion, GitHub, or any remote MCP server into Basedash and the agent can take action on the data it already reads. Connect any app. Act anywhere.

A practical decision framework for startups: when analytics on a production database is fine, when to add a read replica, and when a real warehouse is overdue.

A step-by-step Metabase migration playbook: audit, tool selection, dashboard rebuild, cutover, and decommission. Includes a checklist and common mistakes.

A practical guide for letting ChatGPT, Claude, MCP servers, and custom AI agents query your business data without leaking PII, blowing up your warehouse bill, or giving an LLM root access.

A practical guide to choosing where business logic should live in your data stack: warehouse views, dbt models, a semantic layer, or BI tool calculations. Includes a decision framework.

A practical guide to building a SaaS revenue dashboard. Covers which metrics to include, how to source data from Stripe and your app, layout patterns, and common mistakes.

A practical 30-day BI proof of concept framework with weekly milestones, a 7-criterion scoring rubric, vendor questions, hidden cost checks, and security review steps.

Compare 7 retail analytics platforms for store performance tracking, inventory optimization, demand forecasting, and omnichannel reporting across POS, warehouse, and ecommerce data.

Compare 7 client reporting tools in 2026 — Whatagraph, AgencyAnalytics, Klipfolio, DashThis, Databox, Google Looker Studio, and Basedash — across branding, automation, and pricing.

Today we're launching the Basedash MCP server — a single URL that drops your data analyst into Claude Code, Cursor, ChatGPT, Windsurf, or any MCP-compatible client. Ask data questions where you already work.