Open Source Technologies in the Analytics Revolution (Virtual)

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Meeting ID: 936 1049 7045
Passcode: 908511

One of the hallmarks of modern analytics is that data pipelines are largely built upon open source software (OSS). It is entirely possible to create cutting edge data science, machine learning, data engineering, ETL processing, and predictive analytics pipelines without using any commercial software. Of course, OSS does not necessarily mean “free,” but as a thought experiment, the first part of this session will explore the role of OSS in your data analytics stacks and data pipelines.

For the second half of this discussion, we will examine how OSS tools and platforms can be used to learn and create your own Machine Learning and Data Analytics projects without breaking the bank.

Agenda:
Introductions
Presentation (30 min)
Apache Kylin Demo (10 min)
Q&A

Speakers:
Zitong Wei is passionate about technology that helps solve people’s daily challenges. She has been in computer software for over eight years and is now focused on big data technology. Serving as Principal Solutions Architect at Kyligence, she has helped world famous enterprises across many industries turn their big data assets into valuable insights. Previously, she worked for MZ and eBay where she developed complicated data pipelines and large-scale backend systems.

Rachel Beddor is a Solutions Engineer for Kyligence, where she creates technical content to enhance the learning experience for new Apache Kylin and Kyligence users. She has dedicated her career to making technology more accessible, fun, and inviting to people of all backgrounds.

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