About the Course
Modern audit functions face a critical mandate: provide deeper assurance across larger datasets without expanding headcount. Relying on manual spreadsheets and limited sample sizes leaves critical vulnerabilities unexamined, particularly in high-risk areas like procurement, payroll, and financial reporting. To deliver credible assurance, you must demonstrate specific capabilities: extracting data from disparate ERP systems, validating data integrity, executing full-population testing, identifying statistical outliers, and visualizing risk concentrations. Guided by the ISACA® IT Audit Framework (ITAF) and IIA standards, this training provides the structured approach required to embed analytics directly into your annual audit plan and daily fieldwork.
This program transforms scattered data skills into a repeatable, defensible audit testing system. You will learn how to scope analytics-driven audits, acquire and normalize raw data, execute advanced testing scripts, and present findings to the audit committee. Specifically, you will gain hands-on practice building SQL queries for data extraction, applying Benford's Law for fraud detection, configuring fuzzy matching for duplicate payment identification, and designing Power BI® or Tableau® audit dashboards. While you will be introduced to advanced machine learning concepts for predictive risk modeling, the core focus remains on practical implementation: you will actively practice writing extraction scripts, building continuous monitoring frameworks, and generating automated exception reports that you can deploy immediately.
Implementing data analytics in audit environments often stalls due to fragmented data silos, legacy ERP constraints, and stakeholder pushback regarding data access. This course is explicitly designed for professionals operating under these real-world conditions. You will learn how to navigate data governance hurdles, validate data completeness before testing, and build a compelling business case for continuous auditing tools, ensuring your analytical initiatives deliver measurable ROI and withstand regulatory scrutiny.
Target Audience
This comprehensive training is structured for audit and risk professionals who need to integrate data analytics into their assurance methodologies. It bridges the gap between traditional audit principles and modern data science applications.
This course is designed for:
- Internal Audit Managers overseeing the transition to continuous auditing frameworks
- IT Auditors evaluating data governance and automated control effectiveness
- Fraud Investigators utilizing forensic data analysis to detect financial anomalies
- Financial Auditors executing full-population substantive testing on ledger transactions
- Compliance Officers monitoring real-time regulatory adherence across enterprise systems
- Risk Analysts designing quantitative risk assessment models for audit planning
- Audit Data Scientists building automated exception reporting pipelines
- Quality Assurance Reviewers validating the integrity of audit analytics scripts
- Information Security Auditors analyzing access logs for segregation of duties violations
- Chief Audit Executives reporting data-driven risk insights to the board
Course Objectives
This program provides a rigorous, step-by-step progression from data acquisition to advanced visualization, ensuring you can execute end-to-end analytical audits.
By the end of this course, you'll be able to:
- Assess current audit data maturity using the IIA Data Analytics Framework to identify integration gaps
- Extract transactional data from enterprise ERP systems using SQL queries for full-population testing
- Cleanse raw audit datasets to ensure completeness and accuracy before executing substantive procedures
- Apply Benford's Law and statistical profiling to identify anomalies in financial reporting and procurement
- Execute fuzzy matching algorithms to detect duplicate vendor payments and ghost employee fraud
- Design interactive audit dashboards in Power BI or Tableau to visualize risk concentrations for stakeholders
- Implement continuous auditing scripts to automate routine control testing and exception reporting
- Synthesize complex analytical findings into actionable audit reports that drive management remediation
Requirements & Prerequisites
Participants should have a working knowledge of standard audit methodologies, risk assessment principles, and basic Excel® proficiency. No prior coding or advanced statistical experience is required, as the course introduces data extraction and analysis techniques from the ground up.
Professional and Organizational Impact
Mastering audit data analytics elevates your professional capability, allowing you to deliver undeniable evidence and strategic value to your organization.
As a professional, you will benefit by:
- Build defensible audit conclusions based on full-population testing rather than limited sampling
- Gain technical proficiency in SQL, data visualization, and statistical fraud detection techniques
- Strengthen your credibility with stakeholders by presenting evidence-backed, visual risk insights
- Automate repetitive audit testing procedures to focus your time on high-value risk analysis
- Develop continuous monitoring frameworks that provide real-time assurance over critical controls
- Position yourself as a specialized audit analytics leader capable of driving digital transformation
- Expand your investigative capabilities to uncover complex fraud schemes hidden in massive datasets
Organizations that embed data analytics into their audit functions achieve broader risk coverage, faster issue detection, and more efficient resource allocation.
Your organization will benefit from:
- Reduce audit cycle times by automating data extraction and routine control testing procedures
- Mitigate financial loss by detecting duplicate payments and fraudulent transactions early
- Expand audit coverage to 100% of transactional populations, eliminating sampling risk
- Enhance regulatory compliance through continuous monitoring of critical business processes
- Standardize audit analytics methodologies across the department to ensure consistent quality
- Improve board-level reporting with dynamic risk dashboards that highlight emerging threats
- Maximize the return on existing ERP and data infrastructure investments through targeted analysis
Training Methodology
This is a practical, outcome-driven course designed to turn analytical aspiration into measurable action and credible reporting. We prioritize hands-on application over theoretical discussion.
Methodology includes:
- Hands-on data extraction exercise writing SQL queries to pull general ledger transactions from a simulated ERP
- Scenario simulation requiring the identification of procurement fraud using fuzzy matching and vendor master file analysis
- Diagnostic assessment of your organization's analytics maturity against the ISACA ITAF guidelines
- Stakeholder mapping exercise to negotiate data access protocols with IT and business process owners
- Case study analysis of continuous auditing implementations in the financial services and manufacturing sectors
- Group workshop producing a functional Power BI audit dashboard visualizing payroll anomalies under time constraints
- Reflection exercise challenging traditional sampling methodologies using statistical variance evidence
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Data Analytics for Auditors Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Skills Relevance
- Master cutting-edge data analytics tools essential for modern auditing.
- Transform data into actionable insights to drive audit efficiency and effectiveness.
- Leverage big data techniques to identify financial discrepancies faster than ever.
Expert Delivery
- Learn from industry-leading auditors with decades of real-world experience.
- Courses designed by audit professionals to meet the demands of current industry standards.
- Benefit from personalized feedback on real-world data analytics scenarios.
Career Advancement
- Elevate your resume with advanced analytics skills that top firms demand.
- Unlock new career opportunities in auditing and beyond with certified data proficiency.
- Gain a competitive edge in the job market with a certification in data analytics for auditing.
Industry Tools and Platforms Featured in this Training
The platforms and vendors South Africa teams are running today — taught against real configurations, not generic vendor demos.
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CaseWare IDEA CaseWare International Inc.Widely used by South African internal audit and assurance teams for importing large data sets from ERP systems, running full‑population tests, and automating standard audit analytics such as duplicate payments and Benford’s Law checks.
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ACL Analytics (Galvanize/RS) Diligent CorporationUsed by audit and forensic teams to perform repeatable data tests over high‑volume financial and operational data, supporting continuous auditing and exception reporting aligned with internal audit plans.
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Microsoft Power BI Microsoft CorporationAdopted across South African corporates and public entities to build interactive audit and risk dashboards that visualise anomalies, trends, and key risk indicators for management and audit committees.
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SAP ERP and SAP S/4HANA SAP SECommonly deployed as core finance and operations systems in South African organisations, providing transaction and master‑data sources that auditors extract and analyse for segregation‑of‑duties checks, fraud patterns, and control effectiveness.
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Pastel Partner / Sage 300cloud Sage Group plcWidely used accounting platforms among South African SMEs and mid‑market firms, from which auditors pull general ledger and sub‑ledger data for reconciliations, sampling, and anomaly detection.
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Microsoft Excel Microsoft CorporationRemains the default analytics environment for many internal audit teams, used for data cleaning, pivot‑table analysis, fuzzy matching via formulas, and documentation of audit tests and exception logs.
