I’m Zahra, and I work where data meets people.

I forecast demand for SP5-grade steel bloom and billet ingots (150×150 mm) traded on the commodity exchange, comparing models at two levels: the aggregated market and individual producers.

• GoalFind which forecasting models give the most reliable demand predictions from historical transaction and supply data.
• Tools
  PythonRegressionLassoRandom ForestXGBoostARIMAX
  Evaluated with RMSE, MAE, MSE, R², MAPE, and MASE.
• What I learned
  • Turning a messy, confidential real-world dataset into a clean forecasting problem.
  • Tree-based models performed better on aggregated market data, while classical statistical models were more reliable for individual firms with limited history.

A three-part project: I modeled the process in Visual Paradigm, built the database and relationships in SQL with a full dataset and queries, then created Power BI dashboards with DAX.

• GoalTurn raw operational data into clear, visual answers to real business questions.
• Tools
  Visual ParadigmSQLPower BIDAX
• What I learned
  • Building the full path from process model to database to BI dashboard.
  • Writing SQL to answer questions like the year’s best-selling product or the top shipper to branches.

Over three phases, my team built a full hiring-and-evaluation framework for a Business Analyst role.

• GoalDefine how to recruit, evaluate, and onboard for a role from end to end.
• Tools
  Job analysisInterviewingKPI designOnboarding
• What I learned
  • Translating a role into measurable KPIs.
  • The full cycle from job design to onboarding, across a four-person team.

My team shaped the idea and, over three phases, wrote the business plan, business case, and feasibility study, then pitched it.

• GoalTest whether the idea could stand up as a real business.
• Tools
  Business planFeasibility studyMarket analysisPricing
• What I learned
  • Taking an idea from concept to feasibility.
  • Market and competitor analysis, cost-opportunity thinking, and pricing.

With a partner, we picked a listed stock, researched the company, wrote a report, then applied the course’s valuation calculations to it.

• GoalProduce a grounded valuation and assessment of a real listed company.
• Tools
  Financial analysisValuation
• What I learned
  • Reading a company’s financials and value chain.
  • Applying valuation methods to a real stock.

• GoalFind where the model could run more efficiently.
• Tools
  Statistical quality control
• What I learned
  • Using SQC techniques to spot inefficiencies in a process.

• GoalPlan the center’s operations grounded in a real needs assessment.
• Tools
  Systems analysisNeeds assessment
• What I learned
  • Running a needs assessment and turning it into an operational plan.