Financial Analysis: from data to informed management decisions

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The program covers the full cycle of financial analysis: from data collection to interpretation. CF, BS, P&L, ratios, DCF, NPV, IRR and real-company casework.
Financial Analysis: practical methods for CF, BS, P&L, DCF, NPV, IRR
Platform:
Laba
Partner courses:
Language of course:
Ukrainian
Difficulty:
Initial
Format of the event:
Online
Certificate:
Yes
Price
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Course overview

Description generated based on course syllabus and open data.

The curriculum systematizes work with financial statements and turns CF, BS, and P&L data into interpretable indicators for management decisions. It includes hands-on tasks on real cases, ratio building, trend analysis, the DuPont model, and cash flow valuation (DCF, NPV, IRR).

Financial analysis: what the program covers

  • CF, BS, P&L: preparation, checks, and cross-statement consistency.
  • Liquidity, turnover, profitability ratios; trend analysis by periods.
  • DuPont model for profitability decomposition.
  • DCF, NPV, IRR: valuation of cash flows and scenario checks.
  • Interpretation of results for management decisions.

Practice on company reports

Work with real statements, build multi-year dynamics, detect drivers of change, and validate hypotheses on data.

Who financial analysis fits / who it does not

  • Fits: finance managers, analysts, business owners, functional leads, accountants moving to FP&A, PMs and product roles working with P&L.
  • Does not fit: those seeking theory only; roles not dealing with numbers or without plans to apply CF/BS/P&L in operations.

Problem → outcome in financial analysis

  • Problem: scattered data, unlinked statements. Outcome: consistent CF–BS–P&L with integrity checks.
  • Problem: unclear profitability sources. Outcome: DuPont-based decomposition and factor analysis.
  • Problem: difficult investment evaluation. Outcome: DCF with NPV, IRR and sensitivity to assumptions.
  • Problem: poor period comparability. Outcome: multi-year trends, normalized data, ratio-based view.

Comparison with alternatives in financial analysis

  • Self-guided content search: fragmented methods without a coherent CF–BS–P&L logic and consistency rules.
  • Accounting-only focus: regulatory reporting without managerial interpretation or DCF methodology.
  • BI-only approach: visuals without DuPont, DCF, or transparent data transformation practices.

Outcomes of mastering financial analysis

  • Linked CF–BS–P&L model and data validation routines.
  • Calculation and interpretation of core ratios.
  • DuPont model for identifying profitability drivers.
  • DCF valuation: NPV, IRR, discount rate, scenarios and sensitivity.
  • Preparation of data-backed conclusions for management decisions.

Tools and cases

Templates for hands-on tasks, real-company case reviews, and a final coherent model with explicit assumptions.

Lecturer

Valentyn Vorobiov: Ex-CFO at Budynok Igrashok, Management Consultant at Centida UK, 20+ years in finance and automation (Nova Poshta, Beeline/Veon, Ukrtelecom, Tespro), implementations in Microsoft Dynamics AX, 1C, SAP; experience with Big4 audits.

Course Description

Metrics and tools Understand how to generate and analyze three key business reports from scratch: CF, BS, P&L. You will calculate business profitability using the Dupont model, discounted cash flow, and the value of cash flows NPV and IRR. Up-to-date knowledge All practical tasks will be consolidated on the lecturer's templates, and the final project will implement the acquired skills at your company.
Lecturer: Valentyn Vorobyov - Ex-Finance Director at Budynok Igrashok, Management Consultant at Centida UK - has 20 years of experience in finance and automation (Budynok Igrashok, Nova Poshta, Beeline, Ukrtelecom, Tespro) - led the implementation team and rebuilt processes for Microsoft Dynamics AX at Nova Poshta - implemented the 1C system at Beeline (Veon Ltd) - implemented SAP at Vodafone - has successful experience in passing Big4 audits - worked his way up from an accountant to a financial director of companies with a staff of more than 23 thousand people

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