Last Updated : 13 Feb 2025

Serverless Data Processing with Dataflow Course Overview

The Serverless Data Processing with Dataflow course provides a comprehensive guide for learners to master data processing architectures leveraging Apache Beam and Google Cloud Dataflow. This course is designed to equip participants with the knowledge required to build scalable and efficient data processing pipelines that cater to their organization's needs without the overhead of server management.

Throughout the modules, learners will delve into the Beam Portability Framework, enabling them to create versatile pipelines that can run across different environments using custom containers. They will explore how to separate compute and storage, manage IAM permissions, quotas, and understand security best practices. The course also revisits core Beam concepts, dives into handling streaming data challenges with windows and watermarks, and discusses the development of custom I/O transformations.

Advanced topics include the use of schemas for structured data, state and timers for complex processing scenarios, and performance optimization strategies. The course also covers robust testing, CI/CD practices, monitoring, logging, error reporting, and troubleshooting methods. Finally, Flex Templates are introduced as a way to standardize and reuse pipeline code, culminating in a comprehensive summary that solidifies the learner's expertise in serverless data processing with Dataflow.

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Flexi Video	16,449
Official E-coursebook
Exam Voucher (optional)
Hands-On-Labs²	4,159
+ GST 18%	4,259
Total Fees (without exam & Labs)	22,359 (INR)
Total Fees (with Labs)	28,359 (INR)

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Schedule personalized sessions based upon your availability.

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Customized Training

Learning without limits. Create custom courses that fit your exact needs, from blended topics to brand-new content.

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Experience exceptional training with the confidence of our Happiness Guarantee, ensuring your satisfaction or a full refund.

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Immerse yourself in a focused learning environment, free from distractions, where you can sharpen your skills in popular global destinations.

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Flexible on-site learning for larger groups. Fly an expert to your location anywhere in the world.

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Target Audience for Serverless Data Processing with Dataflow

The "Serverless Data Processing with Dataflow" course is tailored for IT professionals focusing on scalable, efficient data processing and analytics.

Data Engineers
Cloud Solutions Architects
Software Developers with a focus on data processing
DevOps Engineers involved in CI/CD pipeline optimization
IT Professionals interested in Apache Beam and Google Cloud Dataflow
Technical Project Managers overseeing data processing projects
Data Analysts looking to leverage serverless data processing capabilities
System Administrators managing cloud resources and infrastructure
Business Intelligence Professionals interested in real-time analytics
IT Consultants specializing in cloud-based data solutions
Technical Leads and Team Leads responsible for data processing strategies
Data Scientists requiring large-scale data processing infrastructure
Cloud Security Specialists focusing on secure data processing environments
Quality Assurance Engineers involved in testing data processing pipelines
Technical Support Engineers for troubleshooting and debugging data pipelines
Professionals pursuing Google Cloud certifications related to data engineering

Learning Objectives - What you will Learn in this Serverless Data Processing with Dataflow?

Course Learning Outcomes and Concepts Overview:

This course equips students with comprehensive knowledge and skills for building and managing serverless data processing pipelines using Apache Beam and Dataflow, emphasizing performance, security, and best practices.

Learning Objectives and Outcomes:

Understand how Apache Beam and Dataflow integrate to address complex data processing requirements.
Leverage the Beam Portability Framework to create versatile, cross-platform data pipelines with custom containers.
Optimize data processing by decoupling compute and storage, utilizing Shuffle and Streaming Engine, and employing Flexible Resource Scheduling.
Manage IAM permissions, quotas, and capacity planning effectively for Dataflow jobs to enhance security and efficiency.
Implement security best practices and choose the appropriate zonal data processing strategy for compliance with data locality needs.
Review key Apache Beam concepts, including pipeline construction, PCollections, and PTransforms, to build foundational knowledge.
Employ strategies for handling late data using windows, watermarks, and triggers in streaming pipelines.
Develop custom sources and sinks, optimizing I/O operations for peak pipeline performance.
Simplify pipeline code and boost performance using schemas and structured data.
Utilize state and timers API for complex use cases, ensuring precise data processing control.
Apply best practices for building, monitoring, and troubleshooting Dataflow pipelines to maintain high reliability and performance.
Prototype and execute Dataflow pipelines within Beam notebooks, enhancing pipeline development with interactive tools.
Integrate testing and CI/CD strategies to ensure pipeline quality and streamline deployment processes.
Harness flex templates to create standardized, reusable Dataflow pipeline code, promoting efficiency and consistency across projects.