Journey from Data Modeler to Data Scientist

In this session, we will be talking about what data science is and isn’t, with particular focus on the skills that a data scientist is expected to bring to bear on a problem. We will discuss the educational and skill expectations of a data scientist and how those relate to the skills we’ve developed as ER Modelers.

Going by job descriptions, data science can easily read like “jack of all trades, and master of them all too”. How do we break that down into something more reasonably achievable?

What is data science and what is a data scientist? What do they do?
Do ER Modelers make good Data Scientists?
Are the skill sets complementary?
And more – bring your questions and let’s get into them.

Asoka Diggs is an Enterprise Architect with Intel Corp. in Hillsboro, OR. He has about 15 years of experience in a variety of data management disciplines, including database administration, ER modeling, ETL development, and data architecture. He recently began his own transition to data science when he joined the inaugural class of the Northwestern University MS program in Predictive Analytics. It turns out that there IS something even more fun than ER modeling, and he now spends most of his work time practicing his new analytic modeling skills, and teaching others how to participate and contribute to predictive analytic projects.