Introduction:

In today's increasingly digital and data-driven world, the role of auditors has evolved significantly. Traditional audit techniques are no longer sufficient to handle the complexity and volume of data generated by modern organizations. The Data Analytics for Auditors program, developed by Global Horizon Training Center, is designed to empower auditors with the tools, knowledge, and techniques needed to effectively audit IT systems, databases, and digitalized environments, including those powered by Artificial Intelligence (AI), Internet of Things (IoT), and emerging innovations in digitalization. This hands-on program bridges the gap between traditional audit methodologies and modern data analytics, ensuring participants are well-equipped to conduct insightful, risk-based, and technology-driven audits.

Objectives:

By the end of this program, participants will be able to:

• Understand the fundamentals and importance of data analytics in auditing.

• Apply data analysis techniques to extract, analyze, and visualize audit-relevant information.

• Conduct audits of databases, digital systems, and IT environments using analytical tools.

• Evaluate risks and controls in systems involving AI, IoT, and other digital innovations.

• Leverage modern analytics platforms and tools to enhance audit quality and efficiency.

Organizational Impact:

Implementing data analytics in auditing empowers organizations to:

• Enhance risk management and fraud detection capabilities.

• Improve audit coverage and effectiveness across digital systems.

• Gain real-time insights from operational and financial data.

• Foster a culture of data-driven decision-making.

• Stay ahead of regulatory and compliance standards through innovative audit techniques.

Target Audience:

This program is ideal for:

• Internal and external auditors

• IT auditors and compliance professionals

• Risk management and governance officers

• Audit team leaders and managers

• Professionals involved in digital transformation and data governance

Outlines:

Day 1: Introduction to Data Analytics in Auditing

• Role of data analytics in modern auditing

• Types of audit analytics: descriptive, diagnostic, predictive, prescriptive

• Understanding the audit data lifecycle

• Tools and software used in data analytics for auditing (ACL, Power BI, Python basics, Excel Power Query)

• Legal, ethical, and data privacy considerations

Day 2: Auditing Databases and Digital Systems

• Database structures and common database audit risks

• SQL fundamentals for auditors

• Techniques for data extraction and verification

• Controls and vulnerabilities in digital systems

• Case study: Auditing ERP and financial systems

Day 3: IT Audit Techniques and Digital Innovations

• Overview of IT audit frameworks (COBIT, ISO 27001, NIST)

• Introduction to AI, Machine Learning, and IoT in the audit context

• Auditing AI systems and automation processes

• Cybersecurity risks and control assessment

Day 4: Practical Applications of Audit Data Analytics

• Data sampling, anomaly detection, and fraud analytics

• Key Performance Indicators (KPIs) and data visualization for auditors

• Using Power BI/Tableau for dashboard reporting

• Simulation: Conducting a data-driven audit from planning to reporting

• Review and discussion of real-world audit analytics cases

Day 5: Strategy, Innovation, and the Future of Audit Analytics

• Building an audit analytics strategy and roadmap

• Integrating analytics into the audit cycle

• Impact of emerging technologies (Blockchain, Cloud, AI, IoT) on auditing

• Final assessment, feedback, and certification