How To Operationalize Data Science Projects

Presented by

Dr. Engin Cukuroglu, Data Scientist, Hitachi Vantara

About this talk

Today’s data scientists use machine learning to predict trends, plan ahead of demand and events, and uncover patterns and behaviors. But they spend a significant amount of time on data engineering rather than actual data analysis, delaying the operationalization of machine-learning projects. Find out how you can solve this challenge and help your data scientists be more productive. About our speaker: Dr. Engin Cukuroglu is a data scientist at Hitachi Vantara, Singapore. He received his BS in chemical and biological engineering and has a MS and a doctorate in computational science and engineering. His studies primarily focused on data analytics and big data in protein-protein interactions. After getting his degrees, he analyzed genomic data and developed pipelines for cancer and stem-cell research. His findings have been published in peer-reviewed journals. Dr. Cukuroglu is currently working with rail operators, mining companies, manufacturers, banks, fleet operators and delivery partners in Asia-Pacific to enable their machine-learning and predictive-analytics strategies.

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