Building Resilient Streaming Analytics Systems on Google Cloud - Locales

This course, Building Resilient Streaming Analytics Systems on Google Cloud - Locales, is intended for non-English learners. If you want to take this course in English, please enroll in Building Resilient Streaming Analytics Systems on Google Cloud. 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.

• Introduction
• Course Introduction
• Introduction to Processing Streaming Data
• Processing streaming data
• Introduction to Processing Streaming Data
• Serverless Messaging with Pub/Sub
• Module introduction
• Introduction to Pub/Sub
• Pub/Sub Push versus Pull
• Publishing with Pub/Sub code
• Summary
• Lab Intro: Publish Streaming Data into Pub/Sub
• Streaming Data Processing: Publish Streaming Data into PubSub
• Serverless Messaging with Pub/Sub
• Dataflow Streaming Features
• Module introduction
• Streaming data challenges
• Dataflow windowing
• Lab Intro: Streaming Data Pipelines
• Streaming Data Processing: Streaming Data Pipelines
• Dataflow Streaming Features
• High-Throughput BigQuery and Bigtable Streaming Features
• Module introduction
• Streaming into BigQuery and visualizing results
• Lab intro: Streaming Data Processing: Streaming Analytics and Dashboards
• Streaming Data Processing: Streaming Analytics and Dashboards
• Streaming Analytics and Dashboards
• High-throughput streaming with Cloud Bigtable
• Optimizing Cloud Bigtable performance
• Lab intro: Streaming Data Processing: Streaming Data Pipelines into Bigtable
• Streaming Data Processing: Streaming Data Pipelines into Bigtable
• High-Throughput Streaming with Cloud Bigtable
• Advanced BigQuery Functionality and Performance
• Module introduction
• Analytic window functions
• GIS functions
• Demo: GIS Functions and Mapping with BigQuery
• Performance considerations
• Lab Intro: Optimizing your BigQuery Queries for Performance
• Optimizing your BigQuery Queries for Performance 2.5
• Cost considerations
• Lab Intro: Creating Date-Partitioned Tables in BigQuery
• Partitioned Tables in Google BigQuery
• BigQuery advanced functionality and performance considerations
• Course Summary
• Course summary
• Course Resources
• Building Resilient Streaming Analytics Systems on Google Cloud