The volume and importance of business data and analytics are growing at an exponential rate. Today, more organizations are taking advantage with data science methodologies to understand the current nature of the firm's business operations and strategy as well as predict “what may happen” and be prepared for “what might be a good course of action to take,” based on the application of data analytics.
This program will help you better understand how to leverage data analytics to make decisions and enable business success. Additionally, you will gain a basic understanding of three popularly applied approaches to data analysis.
8:30 a.m. – 4:30 p.m.
September 28-29, 2020
April 7-8, 2021
Cost: $1,695* and includes all class materials, breakfast, lunch and refreshments.
Certificates will be awarded based on successful completion of the 2-day training.
All in-person Open Enrollment Programs can be attended via Zoom. Contact a member of our staff for more information.
* A 20 percent discount will be given to companies that enroll two or more employees.
* A 10 percent discount will be given to TCU staff/faculty/alumni, U.S. veterans
Who Should Attend?
Business leaders, managers, and functional-area knowledge workers at all levels who want to take advantage of the real
opportunity to better utilize data analytics to develop knowledge and insights
that drive improved decision-making.
What You Will Learn
Real life leadership approaches and practical tools you can put into
- Organizational & Strategic Opportunities for Business Analytics
- Business & Functional Applications for Data Analysis & Mining
- Descriptive Statistics
- Data Visualization
How You Will Benefit
- Examine the strategic & operational opportunities for analytics from an organizational and tactical perspective.
- Explore the use of data analytics in the context of specific functional processes and applications such as sales, marketing, HR, finance/accounting, supply chain, and operations.
- Discover how to identify and clearly present results, relationships, trends and other insights using key statistical metrics and tools such as regression analysis, decision trees and cluster analysis – through hands-on exercises.