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. This is the fourth course of the Data Engineering on Google Cloud series.
What you'll learn
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. This is the fourth course of the Data Engineering on Google Cloud series.
Table of contents
- Module introduction 1m
- Streaming into BigQuery and visualizing results 5m
- Lab intro: Streaming Data Processing: Streaming Analytics and Dashboards 0m
- Lab: Streaming Data Processing: Streaming Analytics and Dashboards 0m
- High-throughput streaming with Cloud Bigtable 13m
- Optimizing Cloud Bigtable performance 7m
- Lab intro: Streaming Data Processing: Streaming Data Pipelines into Bigtable 0m
- Lab: Streaming Data Processing: Streaming Data Pipelines into Bigtable 0m
- Module introduction 1m
- Analytic window functions 2m
- GIS functions 3m
- Demo: GIS Functions and Mapping with BigQuery 17m
- Performance considerations 10m
- Lab Intro: Optimizing your BigQuery Queries for Performance 0m
- Lab: Optimizing your BigQuery Queries for Performance 2.5 0m
- Cost considerations 9m
- Lab Intro: Creating Date-Partitioned Tables in BigQuery 0m
- Lab: Partitioned Tables in Google BigQuery 0m
