Auditopia 2026 Arbutus Refresher Training – Pre-Conference

Auditopia Arbutus Training (7 CPE)

The Auditopia Arbutus Training taking place November 10, 2026, is a practical, hands-on workshop designed for auditors, analysts, and professionals who want to strengthen their data analytics skills using Arbutus Analyzer.

In this one-day session, participants will learn how to use Arbutus to analyze data, identify risks, and uncover meaningful insights that support audit and assurance work. The training focuses on practical techniques that can be immediately applied in real audit scenarios.

Through guided demonstrations and real-world examples, attendees will explore how Arbutus can be used to examine large datasets, perform common audit tests, and automate routine analysis tasks. Whether you are new to Arbutus or looking to build confidence in your existing skills, this session will help you better understand how to use the software as part of your everyday audit toolkit.

Participants will leave with practical takeaways, techniques, and ideas they can apply directly at their desk.

Training Highlights

• Practical demonstrations of Arbutus features and audit analytics techniques
• Real-world examples of how auditors use Arbutus in their work
• Tips for analyzing large datasets and identifying anomalies
• Techniques that can be applied immediately in audit and analytics projects

Session Description

This workshop introduces a range of analytical techniques that can expand how participants use Arbutus Analytics to explore, validate, and understand their data. Through practical demonstrations using real-world audit and business scenarios, participants will discover new ways to apply searching, fuzzy matching, classification, summarization, and automation techniques to uncover deeper insights and enhance analytic outcomes.

Learning Objectives

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

• Recognize analytical opportunities where advanced search, fuzzy matching, classification, and automation techniques can provide insights that may be difficult or impossible to obtain using traditional filtering and reporting tools.
• Perform keyword searches to identify risks, exceptions, and anomalies.
• Use fuzzy matching techniques to identify potential duplicates.
• Standardize data using functions to improve same-same-different duplicate testing.
• Normalize addresses to detect non-exact duplicates.
• Segment and analyze populations using multiple approaches with the grouping commands to develop analytic views of data.
• Drill into summarized results to investigate underlying transactions.
• Create reusable analytical workflows and procedures that automate repetitive analysis tasks to reduce manual effort while improving consistency and repeatability.

Field of Study: Computer Software & Applications (6.0 CPE)  ~   Program Knowledge: Intermediate

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