Data Science on Google Cloud Platform: Building Data Pipelines
Data Science on Google Cloud Platform: Building Data Pipelines
.MP4, AVC, 200 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 1h 7m | 152 MB
Instructor: Kumaran Ponnambalam
.MP4, AVC, 200 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 1h 7m | 152 MB
Instructor: Kumaran Ponnambalam
Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by veteran cloud engineering specialist and data scientists Kumaran Ponnambalam—shows how to use the latest technologies in GCP to build a big data pipeline that ingests, transports, and transforms data entirely in the cloud. Learn how to set up data processing jobs using Apache Beam and Cloud Dataflow. Discover how to leverage Cloud Pub/Sub for stream ingestion and real-time messaging. Finally, find out how to process the stream events in Cloud Dataflow. The course uses an end-to-end use case that shows how to apply the knowledge and best practices from the course in a practical data science workflow.
Topics include:
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
Data Science on Google Cloud Platform: Building Data Pipelines
