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Master AI and Machine Learning: From Neural Networks to Applications
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Explore next-generation data modeling, integrity, and governance strategies in this 56-minute podcast episode featuring Doron Porat from Yotpo and Liran Yogev from ZipRecruiter. Dive into their experiences tackling data modeling challenges at scale, including the development of YODA, an internal tool combining developer experience with strong CI/CD and orchestration. Learn about separating modeling and execution layers, implementing data mesh principles, addressing different data personas, and the "shift left" movement in data management. Gain insights on tooling, documenting datasets, and the schema vs. schema-less debate. Discover how organizations can revolutionize their approach to data, with practical takeaways for improving data pipelines, governance, and overall data strategy.
Syllabus
- Intro
- What is Yotpo?
- Building an ETL framework based on Spark
- What is Apache Spark?
- Decoupling the data model
- Using data mesh principles
- How to address different data personas
- What is the "shift left" movement?
- How can organizations change the way they treat their data?
- Use-cases for tooling and documenting data sets
- Schema vs. schema-less
- What is YODA?
- Takeaways from the conversation with Doron and Liran
- It's a wrap!
Taught by
Confluent