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Project 6 — Financial Performance Analysis

Build the financial reporting layer that turns raw transactional and ledger data into the P&L, margin analysis, and variance reporting that finance teams live by.

Overview

Financial analysis is where analytics meets accounting. This project takes company financial data — revenue, costs, budgets, actuals — and produces the reports finance leadership needs: profit and loss statements, margin analysis, budget vs actual variance, and trend forecasting. It's the most "business serious" project and a strong portfolio piece for analysts targeting finance, FP&A, or corporate strategy roles.

Business Objective

Build an automated financial performance dashboard that replaces manual monthly reporting — showing P&L, margins, budget variance, and trends — enabling finance to spend time on analysis rather than spreadsheet assembly.

Tools and Skills

Tool Used for
Excel Financial modelling, variance tables, what-if analysis
SQL Aggregating transactions into financial statements
Power BI Financial dashboard with DAX time intelligence

Difficulty

Intermediate — requires understanding of basic financial concepts (revenue, COGS, gross/net margin, variance) alongside the analytical skills.

Dataset

  • Source: Company financial transactions / a financial sample dataset
  • Options: Microsoft Financial Sample, or a synthetic P&L dataset (revenue, cost, budget by month/department/product)
  • Download: Microsoft Financial Sample
  • Schema details: dataset-guide

Project Files

File Description
business-problem Financial reporting requirements
dataset-guide Dataset schema and financial terminology
data-cleaning Cleaning and structuring financial data
sql-analysis P&L, margin, and variance queries
dashboard-design Power BI financial dashboard
insights-and-recommendations Financial findings and recommendations
interview-questions Project interview questions

Learning Outcomes

  • Understand core financial metrics (revenue, COGS, gross/net margin)
  • Build a P&L statement from transactional data
  • Perform budget vs actual variance analysis
  • Apply time intelligence (YTD, YoY, MoM) in DAX
  • Build a CFO-grade financial dashboard

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