Real-world data integration patterns on Google Cloud

Google Learning
Learn the basics of Google Cloud Data Integration. How do you go from basic, hardcoded data pipelines to making your solution is dynamic and reusable? How do you parameterize your pipelines? What is the difference between parameters and variables, and when should you use them?

Explore some common design patterns for moving and orchestrating data, including incremental and metadata-driven pipelines. Discover best practices and lessons learned and highlight common data engineering best practices for building scalable and high-performing data integration solutions.

Speaker: Nitin Motgi

Watch more:
Google Cloud Next ’20: OnAir → https://goo.gle/next2020

Subscribe to the GCP Channel → https://goo.gle/GCP

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DA214
product: BigQuery, Cloud Pub/Sub, Cloud Dataproc; fullname: Nitin Motgi;

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