Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Omer Sagi

Omer Sagi
Data Scientist, Dell

Omer Sagi is a senior data scientist on the data science team at Dell, where he leads several data science projects in the fields of precision agriculture, online marketing, failure prediction, and text classification. Omer has also taught courses on Java programing and databases. He holds a master’s degree from the Department of Industrial Engineering at Ben-Gurion University; his thesis presented a novel approach for assessing the monetary damages of data loss incidents. Omar is currently a PhD candidate in the Department of Software and Information Systems Engineering at Ben-Gurion University, focusing on developing algorithms that simplify ensemble models.

Sessions

16:35–17:15 Wednesday, 23 May 2018
Improving DevOps and QA efficiency using machine learning and NLP methods
Data engineering and architecture, Data-driven business management, Streaming systems and real-time applications
 Location: S11B Level: Intermediate
Secondary topics:  Text and Language processing and analysis
Ran Taig (Dell), Omer Sagi (Dell)
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DevOps and QA engineers spend a significant amount of time investigating reoccurring issues. These issues are often represented by large configuration and log files, so the process of investigating whether two issues are duplicates can be a very tedious task. Ran Taig and Omer Sagi outline a solution that leverages NLP and machine learning algorithms to automatically identify duplicate issues. Read more.