Inventory Operations Data Analysis

Operations data pulled straight from our inventory-management system needs a clear, story-driven analysis. I will provide raw exports (CSV/Excel) that capture SKU identifiers, on-hand quantities, reorder points, inbound purchase orders and daily movement logs. The task is to turn these numbers into reliable insights that help the team understand where stock sits today, how it has been moving, and what actions will keep us balanced going forward.

The work involves cleaning the data, exploring patterns, flagging anomalies and summarising the findings in plain language. Interactive visuals built in Power BI, Tableau or a similarly robust tool are essential so we can slice the results by warehouse, product category and date range. SQL, Python or R can be used behind the scenes—whatever delivers the most accurate, reproducible output.

Acceptance criteria:
• A fully documented, cleaned dataset ready for future queries.
• An analysis report that highlights key takeaways and explains methodology.
• A live dashboard (or well-structured workbook) that refreshes easily with new data.
• Actionable recommendations tied directly to the evidence uncovered.

I will be available to answer domain questions quickly and can schedule checkpoint reviews to keep the project on course.