About the course

This course is the full version of the complete, end-to-end Finance Analytics portfolio project designed to reflect how analytics work is actually done inside modern finance teams.

You step into the role of a Finance Data Analyst supporting a growing organization, working from business questions through data preparation, KPI modeling, advanced analytics and executive-ready reporting. Rather than focusing on tools in isolation, the project emphasizes analytical reasoning, structure and decision support.

You will build the solution from the ground up by setting up your environment, understanding the business context, preparing layered financial data, defining KPIs and business logic, applying forecasting and scenario analysis and finally designing dashboards that leadership can use to evaluate performance and make forward-looking decisions.

By the end of the course, you’ll have a credible, interview-ready portfolio project that demonstrates how you think, model and communicate as a finance-focused data professional.

What You Will Learn

This project follows the same workflow used in real finance analytics teams, moving step-by-step from context to insight.‍

📌 Business & Finance Foundations
‍- Framing analytics around real business objectives and financial questions
- Understanding P&L structures, cost drivers, and profitability logic
- Translating stakeholder needs into analytical requirements
- Defining meaningful KPIs tied to business outcomes
- Connecting budgeting, actuals, variance analysis, and performance tracking‍

📌 Data Ingestion, Modeling & Quality
‍- Structuring financial data using a Bronze → Silver → Gold approach
- Loading and transforming data using SQL and analytical best practices
- Designing a finance-focused star schema with fact and dimension tables
- Validating data quality to ensure trustworthy reporting
- Creating a solid analytical foundation that scales beyond dashboards

📌 Analytics & Decision Support
- Trend analysis and performance diagnostics
- Forecasting revenue and operating profit
- Scenario and sensitivity analysis for planning and risk assessment
- Combining descriptive and predictive analytics to support decisions‍

📌 Dashboard Design & Storytelling
- Designing executive-ready Power BI dashboards
- Structuring reports around financial logic, not visuals alone
- Enabling drill-downs for deeper operational analysis
- Communicating insights clearly and responsibly to stakeholders

📌 Portfolio & Career Positioning
- Explaining your analytical approach and trade-offs with confidence
- Presenting results in a way hiring managers expect
- Turning technical work into a clear portfolio narrative
- Positioning yourself as a business-minded data professional

Outcome

This project follows the same workflow used in real finance analytics teams, moving step-by-step from context to insight.

By the end of this course, you’ll be able to clearly explain:

- How you structured and prepared the data
- Why specific KPIs and models were chosen
- What insights emerged from the analysis
- And how those insights support real business decisions

You’ll finish with a portfolio project that demonstrates how analytics work is done in practice and one you can confidently showcase in interviews.