Case study on 100K+ real e-commerce orders (Olist dataset): why did revenue growth stop? I built a 6-page Power BI diagnostic star schema, 25+ DAX measures (revenue decomposition into volume vs. basket effects, MoM/YoY, CROSSFILTER) plus a plain-English executive report with a 30/60/90 action plan. Key findings: orders flatlined at 6.6K/month; 97% of buyers never return; one region carries 38.4% of revenue; one category hides a 15.7% decline. Full pipeline on GitHub: Python ETL, SQL validation, dashboard, report.
Real estate dashboards are usually built for data entry. Aurex Living was built for decision-making.
$873,42.39 total revenue. 1,269 completed deals this month. $276K sold, $346K rented. Property cards, agent tracking, map view, average sale value trending +10% - every number a real estate operator actually needs, on one clean white canvas.
I recently built a retail analytics dashboard using Power BI, with data cleaning and transformation using Excel/Power Query.
I'm currently looking to work with small businesses, retailers, and growing teams that want their data to be easier to understand and use.
💬 If you already maintain your business data in Excel, feel free to message me. I'd be happy to show you what a dashboard could look like for your business.