Course overview
Finance teams often hold the evidence needed to explain margin movements, working-capital pressure, control exceptions and forecast variance, but it is scattered across ledgers, subledgers, budget files and operational data. Manual spreadsheet reporting can consume reporting cycles while leaving reviewers unable to trace calculations, test data quality or identify the transactions behind a result. Accounting analytics provides a disciplined way to turn accounting data into repeatable analysis, management reporting and audit-ready evidence.
This course teaches participants to structure accounting data in Excel, clean and combine source files with Power Query, model financial data in Power BI and write DAX measures for core accounting metrics. Participants analyse general-ledger transactions, accounts receivable ageing, accounts payable, revenue, expenses, budgets and cash-flow drivers. The course covers reconciliation logic, exception testing, variance analysis, materiality-based investigation, data modelling and dashboard design for finance users.
Instruction combines short technical briefings with guided case work based on realistic finance datasets, including monthly close, receivables collection, expense control and budget performance. Participants build formulas, queries, models and visual reports while discussing controls over source data, refresh procedures and review evidence. They leave with a reusable accounting analytics workbook and Power BI reporting model structure, supported by calculation logic, data-quality checks and a reporting design checklist.
The course is suited to accounting and finance professionals who already work with spreadsheet-based reports and need stronger methods for analysing larger datasets, producing repeatable management information and explaining financial results with evidence.
