data-analysis

Name: data-analysis
Availability: InStock
Author: sxd007

Detect anomalies and patterns in financial or operational datasets.

2|Updated Jun 26, 2026

Search Tags:#audit #data analysis #anomaly detection #forensic accounting #benford's law #fraud investigation

Ready to run

npx skills add https://github.com/sxd007/investigation-ontology --skill data-analysis-sxd007

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/sxd007/investigation-ontology/tree/main/skills/data-analysis
Command: npx skills add https://github.com/sxd007/investigation-ontology --skill data-analysis-sxd007

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill addresses the challenge of identifying fraud, errors, or operational inefficiencies within large, complex datasets by providing a structured framework for forensic data analysis.

Core Features & Use Cases

Automated Anomaly Detection: Apply statistical methods like Benford's Law and outlier detection to flag suspicious transactions.
Strategic Data Planning: Proactively define data requirements and acquisition strategies for investigations where data is not yet available.
Use Case: A forensic auditor can use this skill to analyze procurement logs to identify potential bid-rigging patterns or duplicate payments, ensuring evidence-based conclusions.

Quick Start

Use the data-analysis skill to perform an exploratory analysis on the provided transaction dataset to identify potential anomalies.

Frequently Asked Questions about data-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I use Benford's Law for anomaly detection in financial datasets?▼

Forensic data analysis applies automated statistical methods like Benford's Law and outlier detection to financial datasets, flagging suspicious transactions. It provides structured evidence generation and audit-ready reporting to identify fraud or operational inefficiencies.

Can I perform forensic accounting on procurement logs to find bid-rigging patterns?▼

Yes, forensic accounting on procurement logs identifies potential bid-rigging patterns or duplicate payments. The analysis applies statistical validation to operational datasets, ensuring evidence-based conclusions for structured audit procedures.

What is the best way to plan data requirements for a fraud investigation?▼

Strategic data planning defines missing information requirements and acquisition strategies proactively for fraud investigations. This requirement-driven approach ensures proper data collection before conducting statistical validation and audit-ready reporting.

Does this forensic data analysis approach support audit-ready reporting?▼

Yes, forensic data analysis supports audit-ready reporting by satisfying requirements for structured evidence generation and statistical validation. It processes operational datasets to detect trends, patterns, and anomalies suitable for formal audit procedures.

When do I need anomaly detection for operational datasets?▼

Anomaly detection for operational datasets is needed when facing large, complex records containing hidden fraud, errors, or inefficiencies. It applies statistical methods to flag suspicious transactions and uncover trends requiring investigation.