From ETL design to Tableau delivery — how to build BI that gets used, trusted, and actually drives decisions rather than decorating slide decks.
I’ve built BI for Sales, Finance, Operations, Marketing, Technology, and Customer Support — across Tableau, Snowflake, Salesforce, and ConnectWise. After enough of these projects, the pattern is clear.
The technology is rarely the problem. Most BI failures are people and process failures — unclear metric definitions, no stakeholder alignment before build, no governance to keep it maintained once it’s live.
This pillar covers how to build BI that actually gets used — from the data model up through the dashboard layer to the governance that keeps it trusted over time.
How to design dashboards that drive decisions — KPI selection, layout, audience-specific views, and the checklist that separates informative from decorative.
Building the pipeline behind the dashboard — multi-source ETL from CRM, PSA, and SharePoint into Snowflake. How to design it for reliability, not just launch day.
Building and maintaining a Tableau environment that stays trustworthy — the audit process, report retirement, certified data standards, and the governance layer that prevents the report graveyard.
Before the AI model could work, the data had to be right. Getting to 89% triage accuracy required clean, consistent ticket data flowing from the right sources — which meant solving BI and data quality problems first. The downstream reporting layer then turned 54,821 AI predictions into a financial case that leadership could act on.
The result: $200K in year-one savings, 6 FTE workloads replaced, and a reporting infrastructure that made the ROI legible to finance — not just to the ops team that built it.