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