Data Engineering, Finance and AI
You don't need an IT department to build a BI solution. With the right tools and governance, finance teams can own their data pipeline from source to dashboard.
The average month-end close takes 6-7 business days. Top performers do it in 3-5. Some companies have cut it to 2 days with automation. Here's how.
How to wire n8n, Power BI, and the Model Context Protocol together for an automated data pipeline that feeds AI-generated insights directly into your dashboards.
Finance teams build dashboards around available data. CFOs need dashboards built around decisions. Here's the gap — and how to close it.
When you're reconciling $150M+ in annual transactions across multiple systems, manual processes break. Here's what I learned about building automated reconciliation that actually works.
Power BI handles 400GB datasets versus Excel's 1-million-row limit, reducing reporting time by 60-80%. Here's the migration playbook from someone who's done it.
91% of financial firms are now adopting AI for core operations. But using AI without proper governance is a career risk. Here's how to use AI safely in finance.
Small businesses using n8n report saving 15+ hours weekly and cutting operational costs by 15-25%. Here are 5 specific finance workflows you can automate this week.
Power BI Pro handles most reporting needs. But when you hit data volume limits, need real-time processing, or want AI integration — Fabric changes the equation. Here's the honest breakdown.
Finance teams spend months building Power BI dashboards that nobody uses. Here are the 5 most common mistakes and how to fix them — from someone who's seen both sides.
A solo consultant built an autonomous AI agent team on a $50 Raspberry Pi — handling finance reporting, web management, and operations 24/7. Here's the architecture and real results.
A step-by-step breakdown of how I replaced manual finance workflows with a fully automated Power BI + n8n pipeline that handles $150M in annual expenses — saving 40+ hours per month.
