Excel Projects
Build reporting and analysis projects.
MIS Collection Dashboard — Build a practical branch-and-employee collection report from raw MIS data, then turn it into a management dashboard.
Loan Ageing Report — Turn due-date and DPD data into ageing buckets, risk flags and a management summary.
Sales Performance Tracker — Measure employee sales against targets and identify the strongest and weakest performers.
Data Cleaning Challenge — Clean a deliberately messy employee master and prepare it for reliable reporting.
Monthly Reporting Automation — Design a repeatable Power Query workflow for combining monthly files into one reporting table.
Power Pivot Business Model — Build a small data model with branches and transactions, then define reusable measures.
Executive MIS Capstone — End-to-end analyst challenge: turn raw monthly business data into a reconciled management view, choose the right analytical tools, and defend the final decision.
Reconciliation Control Room — Reconcile source-system totals against an Excel reporting layer, isolate exceptions and document a sign-off-ready control process.
Forecast & Scenario Dashboard — Build a management forecast model with Base, Upside and Downside scenarios, monthly variance analysis and a decision-focused dashboard.
Dynamic Array Reporting Lab — Build a live management extract using FILTER, SORT, UNIQUE, TAKE and spill-aware formulas instead of manual copy-paste.
Loan Repayment & EMI Model — Build a transparent loan model with EMI, interest/principal split, balance movement and scenario testing.
Data Analyst Interview Case — Complete a timed business-analysis case that combines cleaning, lookups, criteria formulas, PivotTables, charts, QA and executive commentary.
Inventory & Reorder Planning — Turn a stock movement table into an exception report. Reconcile opening, receipts, issues and closing stock before recommending replenishment.
HR Headcount & Training Analytics — Build a department scorecard from synthetic employee records. Compare active headcount, salary totals and training hours, then explain the limits of a small sample.
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