Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.
Acerca de este Curso
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
- 5 stars64,63 %
- 4 stars26,60 %
- 3 stars6,30 %
- 2 stars1,59 %
- 1 star0,86 %
Principales reseñas sobre BUILDING BATCH DATA PIPELINES ON GCP
Good, I think pipelines need to have more labs related to some necessities in the industry, such as connect them to other external sources outside GCP
Excellent course with appropriate explanation on cloud data fusion, data composer, data proc and cloud data-flow. Must learn course for all aspiring Big Data Engineers.
This course really teaches me in-depth about data engineering than the cloud or any other products offered by GCP which is the most important part.
Good introduction to pipelines building in GCP, Starting labs need to be in more detail. Other than that very good course.
¿Puedo acceder a una vista preliminar del curso antes de inscribirme?
¿Qué recibiré cuando me inscriba?
¿Cuándo recibiré mi Certificado de curso?
¿Por qué no puedo participar como oyente en este curso?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.