Audit Data Analytics (ADA) Simulator
Discovering Patterns, Relationships, and Anomalies in Audit Data
The Four Categories of Data Analytics
ADAs can be categorized into four types, each answering a different kind of question and increasing in complexity and value.
1. Descriptive
"What happened?"
Summarizes data to understand past events. Techniques include summary statistics, sorting, and aging.
2. Diagnostic
"Why did it happen?"
Examines data to find root causes. Techniques include drill-down analysis, data mining, and variance analysis.
3. Predictive
"What will happen?"
Uses historical data to forecast future outcomes. Techniques include regression, forecasting, and classification.
4. Prescriptive
"How can we make it happen?"
Recommends actions to optimize outcomes. Techniques include what-if analysis and machine learning.
The 5-Step ADA Process
Applying an ADA follows a structured process to ensure the results are relevant, reliable, and properly evaluated. Click each step to see more details.
Click a step above to see its description.
ADA Simulation: Risk Assessment
Let's simulate a descriptive ADA used for risk assessment. We want to compare quarterly sales across five different store locations to identify any anomalies that might indicate a risk of material misstatement. Click the button to run the analysis and highlight potential areas of concern.
