DA-102 FUNDAMENTALS OF DATA ANALYTICS—HANDS-ON

DA-102 FUNDAMENTALS OF DATA ANALYTICS—HANDS-ON

Description

Internal audit departments are expected to help organizations improve business processes, ensure regulatory compliance, fight fraud, and get to the root cause of organizational issues. Data analytics programs can help audit functions meet those expectations and be more efficient, scalable, reduce testing effort and audit errors, while providing greater assurance and audit and risk coverage. Effective programs provide long-term continuous auditing and monitoring for legal and compliance issues as well as the ability to perform ad hoc audit testing, operational analysis, and fraud investigations. Data analytics programs are the cornerstone of fraud detection for many organizations, providing audit and fraud teams the ability to identify red flags in real time.

 

This course teaches participants to develop data analytics scripts to support an audit. The course is interactive, and participants will learn through a combination of lecture, live demonstrations, and hands-on exercises. Bonus: all registered attendees will receive a trial version of the software and best practice templates.

Learning Objectives

  • Importance of planning objectives
  • How to process data from any source
  • Identifying outliers or issues
  • Analyzing data from various sources
  • Applying basic fraud techniques
  • Setup-based repetitive procedures to support continuous auditing/monitoring

 

Course Outline

Overview of Data

  • Data analytics programs | Data concepts
  • Data management best practices | Project organization best practices

Importing Data and Sorting Data

  • Locating data | Data formats | Identifying data integrity issues
  • Arranging data | Determining appropriate fields to sort by

Expressions

  • Returning results based on date, character, and numeric data
  • Creating simple and complex expressions

Functions

  • Learning sophisticated analytical routines that allow you to manipulate data
  • Leveraging to create computed fields or filters
  • Normalizing data in key fields

Filtering

  • Comparing the values in a field with a constant or with values in another field
  • Find needles in a haystack

Computed Fields

  • Virtual fields that use data derived from a calculation
  • Performing calculations without altering the original data

Profiling and Grouping Data

  • Understanding the data | Gaining insights into the business
  • Organizing data based on type, numeric, character, and date

Comparing Data

  • Stacking data from multiple sources
  • Side-by-side data from various sources

Fraud Techniques

  • Duplicates | Fuzzy logic | Benford’s law
  • Compliance testing and verification
  • Red flag attributes

Repetitive Analytics

  • How to automate processes
  • Developing interactive procedures
Duration

CPE

Delivery

Field

Level

Who Should Attend

 

Prerequisites

Advanced Preparation

2 Days

16

Group-Live

Auditing

Intermediate

Internal auditor staff and management; financial and operational management and staff

Professionals with at least 2 years of experience

None