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 stars67.39%
- 4 stars25.58%
- 3 stars5.43%
- 2 stars1.33%
- 1 star0.25%
TOP REVIEWS FROM BUILDING RESILIENT STREAMING ANALYTICS SYSTEMS ON GOOGLE CLOUD
It was really good experience as always at Google cloud platform. Thanks for the team for materials and great course content. appreciated.
Very useful course for data engineers specially covered lot of ways to optimize sql in bigquery
An excellent course. A great way to teach building streaming data pipelines and optimizing queries on BigQuery and BigTable (by , inter alia, partitioning data sets )through hands-on labs.
This course describes in a deep way the main concepts of streaming processing on GCP. The updates respect to previous course are very relevant.
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