Data Analytics: From Data to Wisdom

Course Overview

CPE Credits: 8
Prerequisites: None
Learning Level: Basic
Instructional Method: Group/Live
Field of Study: Information Technology – Technical

Course Revision Date: March 1, 2023

Course Description

In today’s business world, data is easier than ever to collect and store. While the management of this big data is increasingly important to the decision makers in the organization, big data is progressively more difficult to analyze. As increasingly more and more organizations look to utilizing their data in support of strategic decisions and to build data-intensive products and services, data analytics is rapidly becoming a critical business process.

This presentation will cover the basic concepts of data analytics, big data, and methodologies for analyzing structured and unstructured data, as well as addressing a wide range of data analytic techniques and concepts.

Discussion is structured around the broad frameworks of the different types of data analytics, namely, descriptive, diagnostic, predictive and prescriptive analytics. The increasing usage of data analytics, for audit applications within the internal audit function, will also be examined.

Audience

This course is intended for internal and external audit professionals, project managers, system and business analysts, end user decision makers, Info Sec professionals, and those professionals who need an understanding of data analytic applications and have an interest in assessing and establishing well-designed data analytic programs, be it for public, private enterprises or government agencies.

Objectives

After completing this course, participants will be able to:

Understand why “big data” is so important in today’s business decisions.
Comprehend the basics of analytics by learning key terms, concepts and knowledge areas.
Describe, with examples, the various components of business intelligence and knowledge management.
Present what data mining is and is not.
Explain business analytics (why, what, how), Volume, Velocity, and Variety, and Big Data.
Identify the tools needed to examine large datasets.
Explain the use of analytics in decision making (scorecards and dashboards).
Discuss visual representation methods and techniques that increase the understanding of complex data and models.
Interpret and present visually, orally and in written form, valid conclusions drawn from data analysis.
Determine which analytical method to apply given the nature of the problem and available data.

Course Outline

Please contact Al with a request for a detailed course outline…

albert@bac-mail.com

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