Processing streaming data is becoming increasingly popular as streaming enables businesses to get real-time metrics on business operations. This course covers how to build streaming data pipelines on Google Cloud. Pub/Sub is described for handling incoming streaming data. The course also covers how to apply aggregations and transformations to streaming data using Dataflow, and how to store processed records to BigQuery or Cloud Bigtable for analysis. Learners will get hands-on experience building streaming data pipeline components on Google Cloud using QwikLabs.
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About this Course
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Try Coursera for BusinessWhat you will learn
Interpret use-cases for real-time streaming analytics.
Manage data events using the Pub/Sub asynchronous messaging service.
Write streaming pipelines and run transformations where necessary.
Interoperate Dataflow, BigQuery and Pub/Sub for real-time streaming and analysis
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Syllabus - What you will learn from this course
Introduction
Introduction to Processing Streaming Data
Serverless Messaging with Pub/Sub
Dataflow Streaming Features
High-Throughput BigQuery and Bigtable Streaming Features
Advanced BigQuery Functionality and Performance
Summary
Reviews
- 5 stars67.33%
- 4 stars25.64%
- 3 stars5.43%
- 2 stars1.33%
- 1 star0.25%
TOP REVIEWS FROM BUILDING RESILIENT STREAMING ANALYTICS SYSTEMS ON GOOGLE CLOUD
Clair et complet
C'est parce qu'il y a ce genre de contenu que je progresse beaucoup plus vite sur GCP que sur les autres plateformes.
The most compacted and impacted course in data engineering with abundance of resources. A lot to learn from this course.
Another excellent course. Many opportunities to use Cloud Dataflow and effective ways of using Google's big data warehouse, BigQuery.
It was really good experience as always at Google cloud platform. Thanks for the team for materials and great course content. appreciated.
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