Business Analytics


Day Program - CBA 350

Fall Session 2017
Oct 16 - Oct 18, 2017 

Spring Session 2018
Apr 2 - Apr 4, 2018  

Schedule: Three Days, Monday - Wednesday, 8:30 a.m. to 4 p.m.
Tuition:
$1,375  /   CEUs:  1.8 


Online Program - CBA 450


Schedule: Online, Anytime
Tuition:
$1,375  /   CEUs:  1.8 


Overview

The 21st century belongs to those who can think and act based on sound business intelligence. Organizations need to make business decisions based on more than feelings or gut reactions to events – regardless of the field. Consumer product companies, insurance companies, banks, governments, and even sports teams are utilizing analytics to improve their bottom line and assure their long term success.

This course focuses on business analytics as a process for transforming data sourcing/management and data integration into meaningful business intelligence.

This course directly supports the BIA segment of the (CBIP) Certification Exam (CBIP Certified Business Intelligence Professional Exam).

Who Should Attend

Business executives, owners, and managers seeking an improved understanding of business intelligence and business analytics practices. It is also designed for business analysts or process managers, business or technical systems analysts, requirements engineers, product managers, product owners, enterprise analysts, business architects, management consultant/change agents, or a practitioner in a related discipline such as project management, software development, and quality assurance or interaction design.

Objectives

This course will teach you how to transform data to meaningful business intelligence in order to make sound business decisions. You will learn and understand the relationships between business process performance, integration, and business performance metrics. You will learn how to set up a business metrics dashboard to examine and understand the relationship between business intelligence and business analytics. As important, you will learn how to best interpret what the data represents by extracting the meaningless data to avoid misinterpretation of “real” data required to make better decisions.

Topics

  • Descriptive Statistics
  • Data Exploration
  • Probability
  • Inferential Methods
  • Regression Analysis
  • Predictive Analytics & Models

Our program also includes the study of predictive analytics. Predictive models and analysis are typically used to forecast future probabilities. We introduce and discuss a number of techniques, including data mining, statistical modeling, and machine learning to help analysts make future business forecasts.

Key Topics

  • Develop a strategically based, performance metrics dashboard
  • Understand what the analytical age means
  • Develop the ability to make an information strategy
  • Discuss and understand BA concepts, definitions, and terminology following a BA Model
  • Discuss Business Analytics as a holistic information discipline: Combination of IT technologies, human competencies, and organizational processes
  • Understand and apply the application of predictive analytics
  • Understand the practical use of statistical modeling applied to business analytics
  • Discuss and understand the different types of dashboards
  • Discuss good and bad dashboard designs