- GCP products for data pipelines
- Setting up a pipeline with Apache Beam and Cloud Dataflow
- Processing data with Beam and Dataflow
- Ingesting streams with Cloud Pub/Sub
- Performing stream analysis with Dataflow
Skill Level Intermediate
- [Kumaran] Data science is the key technology for any IT professional. More and more data science applications are being built today, and they are being built on cloud platforms, like Amazon Web Services, Google Cloud Platform, and Microsoft Azure. Cloud brings unlimited scalability and elasticity to data science. Expertise in these platforms is essential to an IT professional.
In my course, I will explore the technologies available on Google Cloud Platform for building big data pipelines that ingest, transport, and transform data in the cloud to enable data science. You need prior familiarity with the basics of the GCP platform, as well as Python programming. So join me, Kumaran Ponnambalam, in my course. Let's explore and experience the options for building big data pipelines.
Node.js: Deploying Applicationswith Kirsten Hunter1h 24m Intermediate
Node.js: Securing RESTful APIswith Emmanuel Henri1h 21m Intermediate
Node.js: Debugging and Performance Tuningwith Jon Peck2h 44m Intermediate
Data science modules covered2m 10s
1. GCP Data Pipeline Products
2. Apache Beam
3. Setting Up Dataflow
4. Data Processing with Beam and Dataflow
5. Cloud Pub/Sub
6. Streaming with Dataflow
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