A Data Science Competency Model – Data Science Skills for Success
Data Science is a very exciting field. It is multi disciplinary and it will literally impact every industry and every functional role within organizations. However, as Data Science starts taking center stage in driving business strategies, organizations are facing the challenges of defining this emerging role, and understanding what are the right skills for hiring and for potentially re-skilling the existing workforce. Join this session to learn more about the Data Science Competency Model and the skills required for successful data science implementations, and to discuss innovative ideas to address the existing data science skills shortage.
This dynamic exchange of the industries best and worst Data Science practices will explore three key areas:
Business Understanding: How to frame a business problem into a Data Science problem and not end up with a costly Business Misunderstanding
The Do’s and Don’ts of Data Modeling and Data Cleaning
Model Validation – Paradoxes and Pitfalls
Bring your examples and stories to share as we collaboratively develop the Data Science body of knowledge.
In this session, we will present examples of the application of Business Analytics to real world supply chain problems and discuss issues, risks, and lessons learned. It will include a view into Arizona State University’s Masters of Science Business Analytics programs focusing on experiential learning through Capstone Projects.