Closing the Data Debt in Industrial AI - How to Convert Data Spaghetti to High Quality Data Sets and Start Delivering Impact
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In this webinar, we will explore the challenges of industrial analytics, and how you can overcome your data debt with a targeted data collection and preparation strategy. We will also discuss the value of a high quality data set and how investing a little time on this can reap major rewards for engineers looking to understand and monitor their equipment behaviour.
The unique challenges of industrial data, strategies to improve your data collection and data labeling, how data labeling yields improved insight
ABOUT THE PRESENTER
An engineer turned data scientist, Alexandra finds her passion in bridging the gap between engineers and data science. With a dual master’s in Biomedical Engineering and Computational Methods (RWTH Aachen, Universiteit Gent), Alexandra started her career in Paris as an engineer developing physical simulations for military applications, before moving to Norway where she developed simulations to evaluate subsea equipment and structural integrity for the oil&gas sector. She transitioned to data science in 2016 and was Chief Data Scientist at a Scandinavian consulting firm before co-founding Unifai.
About the Author
Alexandra GundersonCEO and Co-Founder, Unifai
Alexandra is the CEO and co-founder of Unifai, a software company focused on building the tools needed for engineers and data scientists to develop high quality training data for heavy asset industries. Prior to founding Unifai, Alexandra worked as a mechanical engineer with a focus on computational methods for the nuclear, military, and oil & gas industries before transitioning to a career as a data scientist at Arundo Analytics and later as Chief Data Scientist at Atea, a Scandinavian IT provider