M&A Data Preparation and Valuation Analysis

In mergers and acquisitions, raw financial data is rarely ready for immediate analysis. To make sound strategic decisions, you must know how to identify discrepancies, normalize historical figures, and prepare datasets for rigorous valuation models. This text-based course guides you through the foundational concepts of M&A data preparation, helping you transition from raw financial statements to structured, valuation-ready models. You will learn to spot red flags, adjust for non-recurring items, and apply modern analytical frameworks. What you'll learn: - Understand the core principles of M&A data structures and valuation fundamentals. - Identify and adjust for historical anomalies, non-recurring expenses, and accounting differences. - Clean and normalize complex financial statements using systematic data techniques. - Perform fundamental valuation calculations including discounted cash flow and comparable company analysis. - Assess data quality and identify potential red flags in target company financial disclosures. - Structure raw transaction data into clean, standardized formats for financial modeling. Starting with key M&A terminology and data concepts, you will progress through written case studies and practical data-cleaning scenarios. You will practice restructuring financial statements and calculating key valuation metrics through step-by-step written exercises. This course is designed for aspiring financial analysts, business students, and professionals new to corporate finance, with no prior M&A experience required. Begin reading today to build the practical data skills needed for successful M&A valuations.