A complete book and code pack for learning SQL through finance workflows: ledger data, financial statements, ratios, valuation, forecasting, fraud analytics, and reporting controls.
This is not just an ebook. It includes the guided book and the full FinanceLab project files needed to run the examples locally.
The focus is not generic SQL syntax. The focus is building financial analysis that can be rerun, checked, reconciled, and explained.
Query journal lines, accounts, debit-credit movement, periods, and reporting lines.
Build mapped P&L, balance sheet, and cash flow logic from SQL tables.
Detect duplicated joins, missing mappings, invalid populations, and unreconciled totals.
Calculate profitability, liquidity, leverage, efficiency, and operating measures.
Use SQL and Python for DCF, WACC, NPV, IRR, and sensitivity analysis.
Build revenue forecasting and transaction-risk workflows using SQL and Python.
The project runs locally with Docker, SQL Server, VS Code, CSV files, and Python. The same pattern maps to cloud finance platforms with data lakes, SQL warehouses, semantic layers, Power BI, Excel, controls, and audit evidence.
Everything in one product: the book, the datasets, the SQL Server setup, the database scripts, the chapter SQL files, Python workflows, and controls.
Launch price. Replace this with your final checkout price when ready.
Get the Complete PackageUse the book to understand the workflow. Use the code pack to run the database, scripts, datasets, Python workflows, and reporting controls locally.
Get the Complete Package