At the end of every quarter, Sandra has the same challenge. As the Commercial Analytics Lead at Nestlé Nigeria, she's responsible for preparing performance reports for management. The problem isn't the reporting itself. The problem is that the data comes from different regions. For Q1, sales reports arrived from the North, South-West, and South-East regions as separate CSV files. Each region maintained its own report, which meant slight differences in formatting, naming conventions, and data quality. Before management could answer questions like: • Which region generated the most revenue? • Which products performed best? • Who were the top-performing sales representatives? • How did revenue trend throughout the quarter? The data first had to be prepared. This project started with three regional sales datasets. Using Power Query, I imported the files, standardized the structure, corrected data types, cleaned inconsistencies, and appended all three datasets into a single master table. Once the foundation was in place, I created additional fields to support analysis, including: • Revenue • Profit • Profit Margin • Week Number • Month Name • Performance Indicators With the transformed dataset ready, the next step was analysis. Before building any visuals, I summarized the data using PivotTables to identify the key insights and answer the business questions that mattered most. Only after the analysis phase did I move into dashboard design. I wireframed the layout, defined the KPI structure, selected the appropriate visualizations, and built an interactive dashboard featuring: • Revenue, Profit, Quantity, and Transaction KPIs • Revenue by Channel and Category • Top Performing Sales Representatives • Best Selling Products • Weekly Revenue Trends • Interactive filters for Region, Month, and Sales Representative What began as three separate CSV files became a centralized reporting solution capable of delivering insights in seconds. One lesson I keep reinforcing in my classes: Most people think dashboards start with charts. They don't. Dashboards start with clean data, a structured process, and the right business questions. Tools Used: Excel, Power Query, PivotTables, PivotCharts, Slicers, Dashboard Design #DataAnalytics #Excel #PowerQuery #BusinessIntelligence

Just wrapped up my final project as a Data Analytics Intern at DecodeLabs,a fully interactive Power BI dashboard for Nova Mart e-comm sales. From cleaning raw data, writing SQL queries, to building something dynamic and useful. Here’s what the numbers revealed:

After a few days away, I'm back and picking up right where I left off. Honestly, this week has been really stressful but I finally have the chance to sit down and share this 😅 I completed a 4-page Power BI dashboard on the Sample Superstore dataset — and these are my findings👇

I just finished building a full end-to-end data analytics project and honestly, the messy part was the best part. The project: E-Commerce Revenue Leakage & Profitability Audit The business question: Where is the company thinking it's making money but is actually losing it?