Applying Data Analytics in Accounting

Overview

This course explores how modern technologies are transforming accounting practice. We begin with a survey of accounting fundamentals and emerging analytics topics, including process mining, text analysis, cloud computing, and cybersecurity. Next, we move into visualization, summarization, and filtering techniques for control testing and auditing, using tools like Python and Pandas to analyze and interpret accounting data. We then explore automation in accounting—from generating invoices programmatically to building dashboards from SQL databases—while introducing the spectrum of automation from basic scripts to intelligent agents. Finally, we focus on data governance, covering core principles, lifecycle management, and frameworks like COSO and COBIT, paired with hands-on exercises using SQL and Git to enforce data quality and maintain an audit trail.

Syllabus

Module 1: Survey of Analytics Topics in Accounting

In this module, we will explore the fundamentals of accounting as the language of business, examine key roles and terminology, and consider how emerging technologies and data analytics—from process mining to cybersecurity—are transforming the field.

Module 2: Visualization for Controls and Auditing

In this module, we will plan data analysis steps, explore types and causes of employee fraud, understand internal controls and the role of internal auditors, and apply control testing using tools like Alteryx Designer and Python.

Module 3: Automation in Accounting

In this module, we will explore the fundamentals of automation, identify its applications—particularly in accounting—outline the automation process, and implement basic automation tasks using Python.

Module 4: Data Governance

In this module, we will explore the principles and purpose of data governance, examine common frameworks and internal structures, analyze causes of governance failure, and gain exposure to tools and techniques—including GitHub—for managing data effectively.