Business intelligence consulting for numbers your whole team trusts

Cost depends mostly on how many data sources you have, how clean they are, and how many dashboards and users you need. Real-time requirements, systems without good APIs, and ongoing support after launch also add scope. Software is a separate line: Data Studio and Metabase's open-source edition are free, Power BI and Tableau are licensed per user, and connectors and warehouses are usually billed by usage. We scope and quote after a free consultation and a short look at your systems.

A first production dashboard on three to five data sources typically takes 6–8 weeks, including the KPI workshop, pipelines, testing, and reconciliation to your books. You review working drafts along the way, not just the finished version. Timelines stretch when source data needs cleanup, when a system has no API and we work from exports, or when several people must sign off on definitions. Later dashboards usually go faster because they reuse the same pipelines and models.

We need access to each system that holds your numbers, an admin who can approve connectors, and a few hours of your leaders' time in the first 2 weeks. Typical sources are accounting (QuickBooks Online, Xero, or NetSuite), CRM, e-commerce or POS, scheduling or field service software, and ad platforms. We request read-only access wherever a system supports it. We also ask for the spreadsheets and reports you use today, because they show what people actually rely on.

Usually the one that fits the software you already pay for. Power BI is the natural choice for companies that run on Microsoft 365 and Excel, while Google Data Studio, called Looker Studio until April 2026, is free and strong for marketing and Google Workspace data. Tableau suits teams that do heavy visual analysis or already run Salesforce, and Metabase is simple, can be self-hosted, and embeds well in your own product. The data model underneath matters more than the tool on top.

Yes, once each metric is defined in one governed place. Power BI Copilot, Data Studio's conversational analytics, Metabase's Metabot, and Snowflake Cortex Analyst all turn questions into queries, but without a semantic layer, a single home for metric definitions, they guess at the logic and can be confidently wrong. We build that layer first, then test the assistant against questions with known answers. If your reports use Power BI's older Q&A visual, Microsoft is retiring it at the end of December 2026, and we can move you to Copilot.

Not always. If you report from one or two systems with modest data volume, a direct connection or a well-built spreadsheet can be enough, and we'll tell you so. A warehouse earns its keep when you need to join three or more sources, keep history your systems don't store, reconcile numbers automatically, or run AI and forecasting on clean data. BigQuery or PostgreSQL is often the most cost-effective start for a small or mid-sized company, while Snowflake makes sense when volume or your existing stack calls for it.

You own them, and either your team or ours maintains them. We build in accounts you control wherever possible, document every pipeline and metric, and train the people who will use and update the reports. Your team can take it from there, or you can keep us on a support plan to monitor pipelines, fix broken connectors, add dashboards, and extend the AI features. Either way, nothing is locked inside a system only we can operate.