Building Resilient Streaming Analytics Systems on Google Cloud
Building Resilient Streaming Analytics Systems on Google Cloud
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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 get hands-on experience building streaming data pipeline components on Google Cloud by using QwikLabs.
Course Info
Objectives
- 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
Prerequisites
Experience analyzing and visualizing big data, implementing cloud-based big data solutions, and transforming/processing datasets.
Google Cloud Big Data and Machine Learning Fundamentals (or equivalent experience)
Some knowledge of Java
Audience
This class is intended for data analysts, data scientists and programmers who want to build for out-of-the-ordinary scenarios such as high availability, resiliency, high-throughput, real-time streaming analytics on leveraging Google Cloud.
Available languages
English, 日本語, español (Latinoamérica), français, and português (Brasil)
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Explore Google Cloud content on Coursera and Pluralsight.
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View the public classroom schedule here.
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