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.
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비즈니스를 위한 Coursera 경험해 보기배울 내용
Interpret use-cases for real-time streaming analytics.
Manage data events using the Pub/Sub asynchronous messaging service.
Write streaming pipelines and run transformations where necessary.
Interoperate Dataflow, BigQuery and Pub/Sub for real-time streaming and analysis
직원에게 수요가 높은 기술을 교육하면 회사가 이점을 얻을 수 있습니까?
비즈니스를 위한 Coursera 경험해 보기제공자:
강의 계획표 - 이 강좌에서 배울 내용
Introduction
Introduction to Processing Streaming Data
Serverless Messaging with Pub/Sub
Dataflow Streaming Features
High-Throughput BigQuery and Bigtable Streaming Features
Advanced BigQuery Functionality and Performance
Summary
검토
- 5 stars67.33%
- 4 stars25.62%
- 3 stars5.44%
- 2 stars1.34%
- 1 star0.25%
BUILDING RESILIENT STREAMING ANALYTICS SYSTEMS ON GOOGLE CLOUD의 최상위 리뷰
Sometimes the presenter in week two spoke unclear. Further it was a great course
Great course to understand how to create batch and streaming pipelines to ingest data into data lakes and data warehouses, and advanced bigquery techniques optimization.
This course describes in a deep way the main concepts of streaming processing on GCP. The updates respect to previous course are very relevant.
Very useful course for data engineers specially covered lot of ways to optimize sql in bigquery
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