K2's Data Analytics for Accountants and Auditors - (4 hours) On Demand

$129.00

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 the field of auditing, where internal and external auditors are increasingly turning to data analytics to identify situations requiring follow-up and investigation. Those who understand how to take advantage of various tools that are available to them to assist in these efforts benefit by conducting more thorough analysis and achieving superior results in less time.

In this session, you will learn about various tools and techniques you can use for more thorough analyses of data. Included in the discussion are Excel, various 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!

Major Topics

Differentiating between the four types of data analytics
Analyzing transactional data using Benford’s Law
Utilizing regression analysis in auditing contexts
Identifying and resolving quality of data issues
Working with Power Query, Power BI, and various Excel add-ins for better results in less time

Learning Objectives

Upon completing this course, you should be able to:

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

Course Information

CPE credit: Recommended for 4 hours Auditing
Prerequisites: Fundamental knowledge of Excel and personal computer operations
Program level: Intermediate
Advance preparation: None
Who should participate: Accounting and financial professionals, including auditors, desiring to learn more about Data Analytics, including tools and procedures they can use

Instructional Delivery Method: QAS on-demand learning, including review and final exam questions. To earn credit, participants must pass the final exam with a score of 70% or better within one year of registering for this course. Participants may attempt take the final exam up to 10 times.