Architecting Serverless Big Data Solutions Using Google Dataflow
Learn Dataflow: a serverless, fully-managed Big Data processing service. Simplify scaling & resource management for your data pipelines. Explore a modern approach to data architecture.
Course Content
Architecting Serverless Big Data Solutions Using Google Dataflow is a beginner-level Pluralsight course taught by Janani Ravi. It runs 2h 15m, is taught in English, and includes a certificate of completion. Learners rate it 4.2 out of 5 from 19 reviews. It is a paid course, first published August 2024.
Unlock the Power of Serverless Big Data with Google Dataflow
Google Dataflow empowers developers to effortlessly process and transform data using its intuitive APIs. Built on the robust Apache Beam architecture, Dataflow provides a unified platform for both batch processing and stream processing of data.
In Architecting Serverless Big Data Solutions Using Google Dataflow, you'll gain a comprehensive understanding of Cloud Dataflow's capabilities and its innovative programming model.
Course Highlights:
- Serverless Compute Fundamentals: Begin with a solid grasp of how Dataflow enables serverless data processing.
- Apache Beam API Mastery: Learn to build powerful data pipelines using the Apache Beam API, understanding key concepts like data sources, sinks, and transformations.
- Pipeline Architecture & Visualization: Study the stages within a Dataflow pipeline and visualize them as directed-acyclic graphs.
- Hands-on Development (Java & Python): Develop data transformation pipelines using Apache Beam APIs in both Java and Python, executing them locally and on Google Cloud.
- GCP Integration: Integrate Dataflow pipelines with other Google Cloud Platform (GCP) services, including BigQuery, and learn effective monitoring and debugging techniques for optimizing pipeline performance.
- Advanced Pipeline Patterns: Explore advanced pipeline architectures such as branching and pipelines utilizing side inputs.
- Data Aggregation with Windowing: Apply windowing operations to perform sophisticated aggregations on your data streams.
- Code-Free Data Processing: Leverage pre-built Dataflow templates for common operations, enabling data processing without extensive coding.
By the end of this course, you will be proficient in:
- Designing and implementing Dataflow pipelines for data transformation and processing.
- Seamlessly integrating Dataflow pipelines with other Google Cloud services.
- Optimizing pipeline performance through monitoring and debugging.
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