Data Engineering and the Data Science Lifecycle

Everyone wants to be a data scientist. Data modeling is the hottest thing since Tickle Me Elmo. But data scientists don’t work alone. They rely on data engineers to help with data acquisition and data shaping before their model can be developed. They rely on data engineers to deploy their model into production. Once the model is in production, the data engineer’s job isn’t done. The model must be monitored to make sure that it retains its predictive power. And when the model slips, the data engineer and the data scientist need to work together to correct it through retraining or remodeling. Adam Doyle and Matt Ardolino will talk about the data science lifecycle and present an example that can help walk aspiring data engineers through this process.

About the speakers

Adam is a principal and Modern Data Architecture competency lead at Daugherty Business Solutions. As the competency lead, Adam is responsible for capability development and has led a number of internal training sessions and classes. Adam is an organizer for the St. Louis Big Data IDEA (Innovation, Data Engineering, and Analytics) User Group. As an organizer for the St. Louis Big Data IDEA User Group, he has been a frequent speaker and master of ceremonies. Adam has spoken at local and national conferences including the TDWI Leadership Conference, Hadoop Summit, Stampedecon, the HDAA Annual conference, and HIMSS Big Data Health Care Analytics Forum.

Matt Ardolino is a Consultant with Daugherty Business Solutions in St. Louis, Missouri. He has worked in law, healthcare and technology over the last 17 years with a focus on analytics and process improvement. He is currently exploring commercial applications of data science and advanced data architectures. He holds a Master of Business Administration from Bradley University and a Master of Data Science from Indiana University.

Agenda
6:00 - 6:30 - Food and Networking
6:30 - 7:30 - Presentation
7:30 - 7:45 - Questions