Detailed Course Outline
Module 1 - Introduction to Processing Streaming Data
Topics:
- Introduction to processing streaming data
Objectives:
- Explain streaming data processing.
- Describe the challenges with streaming data.
- Identify the Google Cloud products and tools that can help address streaming data challenges.
Module 2 - Serverless Messaging with Pub/Sub
Topics:
- Introduction to Pub/Sub
- Pub/Sub push versus pull
- Publishing with Pub/Sub code
Objectives:
- Describe the Pub/Sub service.
- Explain how Pub/Sub works.
- Simulate real-time streaming sensor data using Pub/Sub
Module 3 - Dataflow Streaming Features
Topics:
- Steaming data challenges
- Dataflow windowing
Objectives:
- Describe the Dataflow service.
- Build a stream processing pipeline for live traffic data.
- Demonstrate how to handle late data by using watermarks, triggers, and accumulation.
Module 4 - High-Throughput BigQuery and Bigtable Streaming Features
Topics:
- Streaming into BigQuery and visualizing results
- High-throughput streaming with Bigtable
- Optimizing Bigtable performance
Objectives:
- Describe how to perform ad hoc analysis on streaming data using BigQuery and dashboards.
- Discuss Cloud Bigtable as a low-latency solution.
- Describe how to architect for Bigtable and how to ingest data into Bigtable.
- Highlight performance considerations for the relevant services.
Module 5 - Advanced BigQuery Functionality and Performance
Topics:
- Analytic window functions
- Geographic Information System (GIS) functions
- Performance considerations
Objectives:
- Review some of BigQuery’s advanced analysis capabilities.
- Discuss ways to improve query performance.