But the next morning, coffee in hand, she clicked the first video. The instructor, a cheerful man with a European accent named Anders, began with something unexpected: "Do not open Power BI yet. First, ask: what story is your data trying to tell?"
Maya had a problem. Every Friday at 3 PM, her boss, Derek, would poke his head into her cubicle and ask the same question: "How did we do this week?"
Old Maya would have cried. New Maya opened Power BI. Her Udemy-built dashboard had already connected to the vendor table. She added a custom column— ETA vs. Actual —and within twenty minutes, she had an interactive report showing which product categories would miss Black Friday targets. power bi in udemy
Derek didn't promote her that day. But he did send a company-wide email: "Effective immediately, all weekly reports will be replaced by Maya’s Power BI dashboard. She’s teaching a workshop next Tuesday. Attendance mandatory."
And every week, Maya would panic. She’d pull three different Excel sheets from the sales drive, a CSV from the CRM, and a handwritten log from the warehouse. Then she’d spend her weekend merging columns, fixing date formats, and building pivot tables. By Monday morning, the answer was already outdated. But the next morning, coffee in hand, she
From then on, no one asked her "How did we do?" again. They just opened the report. And the data told its story—without a single pivot table in sight.
"You’re a data analyst, Maya," Derek said one Friday, not unkindly. "But right now, you’re just a very slow calculator." Every Friday at 3 PM, her boss, Derek,
By Chapter 3 ("Filters and Slicers"), Maya had transformed her messy Excel files into a single, humming data model. By Chapter 6 ("Measures vs. Calculated Columns"), she made a KPI that blinked red when inventory dropped below safety stock.