What will you learn in Building Resilient Streaming Analytics Systems on Google Cloud Course
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Understand real-time streaming use cases and why stream processing is essential.
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Ingest data using Pub/Sub with push/pull messaging patterns and message publishing.
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Develop streaming pipelines in Dataflow: windowing, transformations, and aggregations.
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Stream data into BigQuery and Bigtable for analytics and dashboarding.
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Optimize performance and costs using high-throughput Bigtable and advanced BigQuery features.
Program Overview
Module 1: Course Introduction
⏳ ~1 min
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Topics: Course goals, structure, and preview of streaming analytics on GCP.
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Hands-on: Orientation video.
Module 2: Streaming Data Challenges
⏳ ~9 min
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Topics: Latency, data volume, and real-time analytics demands.
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Hands-on: Introductory quiz.
Module 3: Pub/Sub Messaging
⏳ ~1 h 8 min
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Topics: Pub/Sub fundamentals, push vs pull, message publishing code.
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Hands-on: Lab: Publish streaming data into Pub/Sub.
Module 4: Dataflow Streaming
⏳ ~1–2 h
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Topics: Dataflow windowing, stream pipelines, and transformations.
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Hands-on: Lab: Build Dataflow streaming pipeline.
Module 5: BigQuery & Bigtable Streaming
⏳ ~4 h
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Topics: High-throughput streaming into BigQuery/Bigtable, dashboards.
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Hands-on: Labs for analytics and Bigtable streaming workloads.
Module 6: BigQuery Advanced Features
⏳ ~1 h
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Topics: Window functions, GIS extensions, query performance, cost efficiency.
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Hands-on: Lab: Optimize BigQuery queries.
Module 7: Course Recap
⏳ ~1 min
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Topics: Summary of key pipeline components and gains.
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Job Outlook
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Prepares for roles as Data Engineer, Streaming Analytics Engineer, or Real-Time BI Engineer using GCP streaming tools.
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Ideal for professionals pursuing the Google Cloud Professional Data Engineer certification.
Explore More Learning Paths
Advance your expertise in cloud analytics and real-time data processing with these curated courses, designed to help you build scalable, resilient systems on Google Cloud.
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Related Reading
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What Is Data Management – Explore best practices for organizing, storing, and maintaining high-quality data critical for streaming analytics.
