{
  "id": 5750098,
  "title": "Building an Interactive Excel Dashboard.",
  "url": "https://urgent.news/2026/09/05/building-an-interactive-excel-dashboard",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-09-05T08:59:28.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/kbonymark/building-an-interactive-excel-dashboard-2329"
  },
  "original_language": "en",
  "account": "The project involved cleaning a dataset of 112 products from Jumia Kenya, which included fields for price, discount percentage, review count, and customer rating. The cleaning process focused on fixing issues such as prices stored as text, ratings buried in descriptive text, invalid negative review counts, and 49% of products having no reviews or ratings.\n\nTo enable interactive analysis, the analyst added calculated columns for review and rating categories, as well as discount categories. This feature engineering process required careful consideration of thresholds and handling of edge cases. The analyst built the dashboard using 8 pivot tables from a single shared table named tblCleaned, ensuring all slicers controlled the entire dashboard simultaneously.\n\nThe data revealed some interesting insights. Discount percentage did not correlate with an increase in review count, suggesting discounts alone do not drive engagement. Similarly, there was a very weak positive correlation between ratings and review counts. Price had a slight positive correlation with ratings, but only mid-to-upper-priced items showed the best average rating.\n\nThe most significant finding was that only 16 out of 112 products had strong engagement (14+ reviews), while 90% of heavily discounted products showed low or no engagement. Additionally, 49% of the entire catalog had zero reviews, regardless of discount or price. Even a product like a 120W Cordless Vacuum Cleaner, which had the most reviews in the dataset, received only a low rating of 2.8 stars.\n\nThe project highlighted that discounting alone is not a substitute for product quality or visibility. Despite heavy discounts, many products showed little engagement, while a small number of well-reviewed products demonstrated that solid ratings and real engagement could coexist without steep price cuts. The analyst learned that the cleaning and validation work, which often seemed mundane, was crucial for generating meaningful insights.",
  "summary": "The Setup The dataset: 112 products scraped from Jumia Kenya, with fields for current price, old price, discount percentage, review count, and customer rating. The goal was to clean it, analyze it, and turn it into an interactive Excel dashboard — the kind with slicers and pivot charts, not just static tables. Simple enough on paper. The data had other plans. Cleaning: The Unglamorous Part That…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}