Training on Intermediate Data Analysis for Audit Professionals
Master intermediate data analysis for audit professionals. Learn data analysis techniques to identify anomalies, assess risks, and improve audit efficiency
Next intake
20 Jul 2026 · Nakuru
Duration
5 days
Live instruction
Delivery
Physical + Virtual
Cohort based
Level
Foundation
Working professionals
Certification
NITA reimbursable
For Kenyan cohorts
Language
English
All materials
About this programme
Internal auditing plays a crucial role in risk management, fraud detection, and compliance assurance within organizations. Organizations in a variety of industries use data analytics daily. For instance, internal auditors can use data analytics to find and define risks, outliers and anomalies that could reveal deeper problems. No matter the industry, however, most analysts today rely on software and artificial intelligence to organize large data sets for analysis. Businesses have increasingly complex digitized processes. Data analytics can collect data from these operations and find trends and variances that can help define risks and inefficiencies. It can visualize this information, and auditors can use it to support their findings and suggestions.
Data analytics can improve internal audits, but only with proper planning. Auditors need to select the correct tools and approach or the analysis will not support their work. This course is designed to enhance the data analysis skills of audit professionals, providing them with the necessary tools and techniques to leverage data for effective auditing. The course builds upon foundational knowledge and introduces more advanced concepts in data analysis, empowering participants to extract meaningful insights and detect anomalies in financial data.
Course Duration
5 Days
Who Should Attend
- Internal auditors
- External auditors
- Audit managers and supervisors
- Compliance officers
- Financial analysts
- Risk management professionals
- Professionals involved in audit data analysis
What you'll walk away with
By the end of this course, participants will be able to:
- By the end of this course, participants will be able to:
- Understand and apply intermediate data analysis techniques in audit processes.
- Utilize various data analysis tools and software effectively.
- Interpret and visualize audit data to identify trends and anomalies.
- Conduct comprehensive data-driven audits.
- Enhance decision-making capabilities through data insights.
- Improve efficiency and accuracy in audit reporting.
- Apply ethical considerations and best practices in data analysis.
What we cover, module by module
Module 1: Foundations of Data Analytics in Auditing
- Understanding data analytics in auditing
- Descriptive, diagnostic, and predictive analysis
- Role of big data in modern audits
- Review of core data analysis concepts
- Advanced Excel techniques for auditors
- Data cleaning and preparation methods
- Case Study: Using analytics to improve audit efficiency and coverage
- Practical: Cleaning audit data and applying advanced Excel functions
Module 2: Using Data Across the Audit Lifecycle
- Data-driven audit planning
- Risk assessment using analytics
- Data use during audit execution
- Reporting and continuous monitoring
- Enhancing assurance through real-time analytics
- Case Study: Risk-based auditing using transaction data
- Practical: Applying analytics across each stage of the audit lifecycle
Module 3: Advanced Data Visualization for Auditors
- Introduction to Tableau, Power BI, and visualization tools
- Creating dashboards for audit reporting
- Visual storytelling for audit findings
- KPI and trend visualization for management reporting
- Case Study: Dashboard reporting that improved management decisions
- Practical: Building an interactive audit dashboard
Module 4: Fraud Detection, Anomaly Identification & Predictive Analytics
- Common fraud schemes and red flags
- Statistical techniques for anomaly detection
- Predictive analytics for audit risk assessment
- Integration of analytics tools with audit software
- Case Study: Detecting fraud through transaction analytics
- Practical: Building predictive models for fraud and risk detection
Module 5: Machine Learning, Ethics & Cybersecurity in Auditing
- Introduction to machine learning in auditing
- Fraud detection using machine learning algorithms
- Model interpretation and validation
- Data ethics, privacy, and regulatory compliance
- Cybersecurity risks and secure handling of audit data
- Case Study: Data breach and cyber risks affecting audit processes
- Practical: Developing a secure and ethical analytics framework for audits
Where the change lands
Organizational Impact
-
Boosts audit efficiency and accuracy through data-driven methods
-
Strengthens risk management with early fraud detection
-
Enhances credibility with investors, regulators, and stakeholders
Personal Impact
-
Builds in-demand auditing and data analysis skills
-
Supports career growth into senior and leadership roles
-
Enables direct contribution to financial integrity and compliance
Dates and locations
Upcoming intakes
Every intake is limited to a small cohort. Booking closes when a date fills or three weeks before the start, whichever comes first.
| City | Starts | Ends | Delivery | Book |
|---|---|---|---|---|
NakuruNext | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Kigali | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Accra | 20 Jul 2026 | 24 Jul 2026 | In-Person | Book |
Kisumu | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Johannesburg | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
Dakar | 27 Jul 2026 | 31 Jul 2026 | In-Person | Book |
- NakuruNext
20 Jul → 24 Jul·In-Person
Book this intake - Kigali
20 Jul → 24 Jul·In-Person
Book this intake - Accra
20 Jul → 24 Jul·In-Person
Book this intake - Kisumu
27 Jul → 31 Jul·In-Person
Book this intake - Johannesburg
27 Jul → 31 Jul·In-Person
Book this intake - Dakar
27 Jul → 31 Jul·In-Person
Book this intake
Common questions.
Still not sure? Send us a note and a facilitator will get back to you within a business day.
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For corporate teams
Training 10+ professionals?
We deliver Training on Intermediate Data Analysis for Audit Professionals in-house at your offices, at a venue we arrange, or fully virtual. Customise the curriculum against your KPIs, and get a bespoke price for the cohort size you need.