Analyzed retail sales data to identify key trends and insights. Examined sales variations by day, hour, and location, identified peak times, and calculated monthly revenue. Utilized Pivot Tables and DAX to extract insights and automated data cleaning with Power Query, saving 5 hours of manual effort and increasing report flexibility by 25%.
active 2024-10-23 → 2024-10-23 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-10-23 to 2024-10-23. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
Recent activity
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Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.