K2's Data Analytics for Accountants and Auditors

In the world of “Big Data,” virtually all business professionals have become data analysts, at least to some extent. However, that is particula...

4/8/2024 10:00am - 2:00pm  |  Online  |  CalCPA

Members: $159.00, Non-members: $209.00

CPE Categories: Specialized Knowledge & Applications (4 CPE)

Interest Areas: Technology

Log In

Description

In the world of “Big Data,” virtually all business professionals have become data analysts, at least to some extent. However, that is particularly true in auditing, where internal and external auditors increasingly turn to data analytics to identify situations requiring follow-up and investigation. Those who understand how to take advantage of various tools to assist in these efforts benefit by conducting more thorough analyses and achieving superior results in less time. In this session, you will learn about various tools and techniques you can use for more thorough data analyses. The discussion includes Excel as a data analysis tool, multiple Excel add-ins, and Microsoft’s Power BI application. If you’re seeking to improve your skills in the field of data analytics, this session is the one for you!

Presented by Thomas Stephens

Target Audience

Practitioners and business executives who need to know more about data analytics and their importance

Course Objectives

  • List the four types of data analytics and identify situations in which each can be useful in auditing environments
  • Identify opportunities to use features in Excel to analyze data in the context of auditing
  • Distinguish between Business Intelligence and Data Analytics
  • Differentiate between correlation and causation
  • Cite examples of how Power Query, Power BI and other tools can streamline and enhance Data Analytics

Subjects

  • Understanding the importance of data analytics in modern business environments
  • Generating and interpreting data analytics using everyday applications such as Microsoft Office Excel and Microsoft's Power BI platform
  • Using regression analysis to create and validate forecasts and projections

Prerequisites

Basic knowledge of technology strategy and standards