Serverless Data Processing with Dataflow: Operations from Coursera

What's inside

Syllabus

Introduction

This module covers the course outline

Monitoring

In this module, we learn how to use the Jobs List page to filter for jobs that we want to monitor or investigate. We look at how the Job Graph, Job Info, and Job Metrics tabs collectively provide a comprehensive summary of your Dataflow job. Lastly, we learn how we can use Dataflow’s integration with Metrics Explorer to create alerting policies for Dataflow metrics.

Logging and Error Reporting

In this module, we learn how to use the Log panel at the bottom of both the Job Graph and Job Metrics pages, and learn about the centralized Error Reporting page.

Troubleshooting and Debug

In this module, we learn how to troubleshoot and debug Dataflow pipelines. We will also review the four common modes of failure for Dataflow: failure to build the pipeline, failure to start the pipeline on Dataflow, failure during pipeline execution, and performance issues.

Performance

In this module, we will discuss performance considerations we should be aware of while developing batch and streaming pipelines in Dataflow.

Testing and CI/CD

This module will discuss unit testing your Dataflow pipelines. We also introduce frameworks and features available to streamline your CI/CD workflow for Dataflow pipelines.

Reliabiity

In this module we will discuss methods for building systems that are resilient to corrupted data and data center outages.

Flex Templates

This module covers Flex Templates, a feature that helps data engineering teams standardize and reuse Dataflow pipeline code. Many operational challenges can be solved with Flex Templates.

Summary

This module reviews the topics covered in the course

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Will appeal to data engineers and other professionals who want a more scalable and reliable solution for high-volume data processing

Can be used to automate and improve the efficiency of data processing pipelines

Teaches industry-standard tools and best practices for dataflow management

Taught by Google Cloud Training, who are recognized industry experts

Covers a wide range of topics, from troubleshooting and optimizing pipelines to testing and deployment

Requires some prior knowledge of data engineering and programming

Reviews summary

Practical dataflow course

Learners say this course is insightful and practical, featuring engaging labs. However, students mention the labs are buggy and not always clearly instructed

Engaging and practical hands-on experience in the course

"In-depth, Practical learning through labs."

"Good intermediate course covering the big picture about how to develop data platforms using GCP and Dataflow."

"Labs are keeping up-to-date, but are lacking overall theoretical summary to teach symmatically how each code could work."

Instructions may not always be clear or comprehensive

"Some instruction of lab is not clear or insufficient to complete."

"The speaking of instructors is also not clear. Even the transcript is also incorrect (maybe speechToText). Difficult to follow."

Students may encounter errors or bugs in labs.

"There are many errors in the labs"

"Some of the labs were buggy but suppurt not really willing to help."

"A lot labs with problem and the responsable for support (QWIKLABS) doesn't help."

Career center

Learners who complete Serverless Data Processing with Dataflow: Operations will develop knowledge and skills that may be useful to these careers:

Data Engineer

A Data Engineer develops and manages data pipelines and data infrastructure. This course can help you build a foundation to work with a variety of data sources and big data tools like Beam, Apache Spark, and Hadoop. You will learn how to optimize and monitor data pipelines, and how to ensure the reliability and performance of your pipelines. This course will also help you with performance considerations when developing both batch and streaming pipelines.

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Big Data Engineer

A Big Data Engineer designs and implements architectures for handling massive datasets. This course can help you learn how to work with and manage big data technologies including Dataflow, which is a fully-managed cloud service that lets you build high-throughput streaming and batch data processing pipelines. You will learn how to optimize and monitor pipelines, and how to ensure the reliability of your pipelines, which is critical for managing big data.

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Data Architect

A Data Architect designs, creates, and maintains a data management strategy. This course will help you learn how to manage data processing pipelines and how to build reliable, scalable data systems to handle big data. By learning how to analyze data and apply data governance and security practices, you can become a more effective Data Architect.

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Data Analyst

A Data Analyst studies, cleans, and interprets data to identify patterns and generate insights. This course will help you become a more effective Data Analyst by teaching you how to build and manage data pipelines for both batch and streaming data. You will also learn how to troubleshoot and optimize your pipelines, and how to ensure the reliability of your data management systems.

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Software Engineer

A Software Engineer designs, develops, builds, and tests software. This course may be helpful in your career as a Software Engineer. You will learn more about data processing and about architecting and building scalable data systems with Dataflow. You will also learn how to test your pipelines, and how to optimize and monitor pipelines to ensure reliability.

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Data Scientist

A Data Scientist collects, prepares, and analyzes data to extract meaningful insights. This course may be useful in your career as a Data Scientist as it teaches you how to build and manage data pipelines for both batch and streaming data. By learning best practices for developing reliable and scalable data systems, you can improve your data science skills.

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Cloud Architect

A Cloud Architect designs, deploys, and manages cloud computing systems. This course may be helpful in your career as a Cloud Architect as it teaches you how to architect and build scalable data systems with Dataflow. You will also learn how to test your pipelines, and how to optimize and monitor pipelines to ensure reliability.

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Database Administrator

A Database Administrator designs, creates, and maintains databases. This course may be useful in your career as a Database Administrator as it teaches you how to build and manage data pipelines for both batch and streaming data. By learning best practices for developing reliable and scalable data systems, you can improve your database management skills.

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Business Intelligence Analyst

A Business Intelligence Analyst analyzes data to extract meaningful insights for a business. This course may be helpful in your career as a Business Intelligence Analyst as it teaches you how to build and manage data pipelines for both batch and streaming data. By learning best practices for developing reliable and scalable data systems, you can improve your ability to analyze data and provide meaningful insights to stakeholders.

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Data Integration Specialist

A Data Integration Specialist integrates different data sources into a single, cohesive system. This course may be helpful in your career as a Data Integration Specialist as it teaches you how to build and manage data pipelines for both batch and streaming data. By learning best practices for developing reliable and scalable data systems, you can improve your ability to integrate disparate data sources.

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Data Governance Analyst

A Data Governance Analyst develops and implements data governance policies and procedures. This course may be helpful in your career as a Data Governance Analyst as you will learn how to develop and implement data governance strategies for data pipelines. This course will also help you with performance considerations when developing both batch and streaming pipelines.

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Data ETL Developer

A Data ETL Developer extracts, transforms, and loads (ETL) data from various sources to a destination system. This course may be helpful in your career as a Data ETL Developer as it provides a detailed overview of the data ETL process. This course will also teach you how to build and manage data pipelines, and how to optimize and troubleshoot your pipelines to ensure reliability.

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Security Analyst

A Security Analyst identifies and responds to security threats. This course may be helpful in your career as a Security Analyst as it teaches you how to build and manage data pipelines and how to design and implement data security measures. By learning best practices for developing reliable and secure data systems, you can improve your ability to protect data from unauthorized access and malicious attacks.

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Systems Analyst

A Systems Analyst analyzes and designs systems to meet the needs of an organization. This course may be helpful in your career as a Systems Analyst as it teaches you how to build and manage data pipelines and how to design and implement data systems that are scalable, reliable, and secure.

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Data Warehouse Manager

A Data Warehouse Manager designs, builds, and manages data warehouses. This course may be helpful in your career as a Data Warehouse Manager as you will learn how to design and implement data pipelines to populate a data warehouse. This course will also help you with performance considerations when developing both batch and streaming pipelines.

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