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Building Resilient Streaming Analytics Systems on GCP auf Deutsch

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Specifically teaches skills for streaming data pipelines in Google Cloud Platform

Introduces Google's Cloud Pub/Sub to process incoming streaming data

Demonstrates how to apply data transformations and aggregations with Cloud Dataflow

Trains learners how to store processed data for analysis in BigQuery or Cloud Bigtable

Offers hands-on labs through Qwiklabs to practice building streaming data pipelines

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Reviews summary

Building resilient streaming analytics on gcp

According to learners, this course offers a solid foundation in building resilient streaming analytics systems on Google Cloud Platform. Many appreciate the hands-on experience provided through practical Qwiklabs, which reinforces understanding of key services like Cloud Pub/Sub, Dataflow, BigQuery, and Bigtable. While the course provides a comprehensive overview, some note that a strong technical background and prior familiarity with GCP are beneficial for navigating the complex topics. A few learners found the pacing challenging at times. However, for those with the right prerequisites, it's considered a highly valuable resource for real-world application.

Course material and instruction delivered in German.

"As a German speaker, I appreciated having high-quality GCP content available in my native language."

"The course is entirely in German, which was a clear advantage for me to grasp complex technical terms."

"Content delivery in German was excellent and easy to follow."

Delivers in-depth insights for resilient systems.

"I gained a solid understanding of how to design and implement resilient streaming analytics pipelines."

"The course covers crucial aspects of building robust systems, beyond just basic setup."

"It goes beyond the basics, providing good insights into handling failures and ensuring data integrity."

Comprehensive coverage of essential streaming tools.

"This course gave me a great overview of how to integrate Pub/Sub, Dataflow, and BigQuery for end-to-end streaming."

"I really appreciate the clear explanations of how BigQuery and Bigtable fit into a streaming architecture."

"The modules on Pub/Sub and Dataflow were particularly insightful, explaining their roles in detail."

Reinforces concepts with direct GCP experience.

"The Qwiklabs are invaluable; they truly solidify the theoretical concepts with real-world application on GCP."

"I found the hands-on labs to be the most beneficial part, allowing me to build actual components of a streaming pipeline."

"It's great to get direct experience with Pub/Sub, Dataflow, and BigQuery through the well-structured labs."

Needs ongoing updates due to rapid cloud changes.

"Cloud technologies evolve rapidly, so I hope the course content is continuously updated to stay current."

"It's good to see that the course has been updated; this is crucial for GCP courses."

"Some parts felt slightly behind the very latest GCP features, but overall, it remains highly relevant."

Requires strong technical and GCP background.

"I found this course assumed a bit too much prior knowledge of GCP services; it's not for absolute beginners."

"The pacing was quite fast, especially if you're not already familiar with cloud concepts or data engineering."

"To truly benefit, I'd recommend having some experience with data processing and GCP before starting."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Building Resilient Streaming Analytics Systems on GCP auf Deutsch with these activities:

Review Cloud Pub/Sub Concepts

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Ensure a solid understanding of Cloud Pub/Sub before diving into streaming data pipelines.

Browse courses on Cloud Pub/Sub

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Review the Cloud Pub/Sub documentation
Complete Cloud Pub/Sub quickstarts or tutorials

Read "Designing Data-Intensive Applications"

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Gain a deeper understanding of streaming data processing concepts and best practices.

View Secret Colors on Amazon

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Read Chapters 3-5 on streaming data architectures

Compile a Glossary of Streaming Data Terms

Show steps

Build a deeper understanding of streaming data processing terminology by creating a glossary.

Browse courses on Streaming Data Pipelines

Show steps

Identify key terms related to streaming data pipelines
Write clear and concise definitions for each term
Organize the terms into a coherent glossary

Five other activities

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Show all eight activities

Follow Google Cloud Platform Tutorials

Show steps

Supplement your learning with step-by-step tutorials from Google Cloud Platform.

Browse courses on Streaming Data Pipelines

Show steps

Complete the "Building Streaming Data Pipelines with Google Cloud Platform" tutorial
Explore other tutorials relevant to streaming data processing

Practice Building Streaming Data Pipelines

Show steps

Solidify your understanding of streaming data pipelines by working through practice exercises.

Browse courses on Streaming Data Pipelines

Show steps

Set up your Google Cloud Platform environment
Create a Cloud Pub/Sub topic and subscription
Build a Cloud Dataflow pipeline to process streaming data
Store the processed data in BigQuery or Cloud Bigtable

Join a Study Group

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Enhance your learning and retention by discussing course concepts with peers.

Browse courses on Streaming Data Pipelines

Show steps

Find a study group or create your own
Meet regularly to discuss course material
Collaborate on practice exercises

Attend a Google Cloud Platform Workshop

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Gain hands-on experience and learn from experts in the field.

Browse courses on Streaming Data Pipelines

Show steps

Find a relevant workshop offered by Google Cloud Platform
Attend the workshop and participate actively
Apply what you learn to your own projects

Develop a Streaming Data Pipeline Project

Show steps

Apply your skills to a real-world scenario by building a streaming data pipeline project.

Browse courses on Streaming Data Pipelines

Show steps

Identify a business problem that can be solved using streaming data
Design your streaming data pipeline
Implement your pipeline using Google Cloud Platform
Analyze the results and iterate on your design

Career center

Learners who complete Building Resilient Streaming Analytics Systems on GCP auf Deutsch will develop knowledge and skills that may be useful to these careers:

Streaming Data Engineer

Streaming Data Engineers use their knowledge of cloud-based platforms to manage data pipelines. They are responsible for working with data engineers, data scientists, and other professionals to help build, manage, and maintain streaming data pipelines. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Streaming Data Engineer

Data Engineer

Data Engineers design, build, and maintain data pipelines that process and transform data for analysis. They work with data analysts, data scientists, and other professionals to ensure that data is accurate, consistent, and accessible. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Data Engineer

Cloud Architect

Cloud Architects design, build, and manage cloud computing solutions. They work with customers to understand their business needs and translate them into technical solutions. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Cloud Architect

Big Data Engineer

Big Data Engineers design, build, and maintain big data systems. They work with data scientists, data analysts, and other professionals to manage and process large datasets. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Big Data Engineer

Data Analyst

Data Analysts use data to solve business problems. They work with data engineers, data scientists, and other professionals to analyze data and make recommendations. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use data to build models and make predictions. They work with data analysts, data engineers, and other professionals to develop and implement machine learning solutions. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, develop, and maintain software applications. They work with other engineers, designers, and product managers to create software that meets the needs of users. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Software Engineer

Systems Engineer

Systems Engineers design, build, and maintain computer systems. They work with other engineers, administrators, and users to ensure that systems are reliable, efficient, and secure. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Systems Engineer

DevOps Engineer

DevOps Engineers work with developers and operations teams to ensure that software is deployed and maintained efficiently. They use automation and other tools to improve the software development and delivery process. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for DevOps Engineer

Data Architect

Data Architects design, build, and maintain data architectures. They work with data engineers, data scientists, and other professionals to create data architectures that meet the needs of the business. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Data Architect

Database Administrator

Database Administrators design, build, and maintain databases. They work with other engineers, administrators, and users to ensure that databases are reliable, efficient, and secure. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Database Administrator

Network Engineer

Network Engineers design, build, and maintain computer networks. They work with other engineers, administrators, and users to ensure that networks are reliable, efficient, and secure. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Network Engineer

Security Engineer

Security Engineers design, build, and maintain security systems. They work with other engineers, administrators, and users to ensure that systems are secure from unauthorized access and attack. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Security Engineer

Cloud Security Engineer

Cloud Security Engineers design, build, and maintain security systems for cloud-based applications and data. They work with other engineers, administrators, and users to ensure that cloud-based systems are secure from unauthorized access and attack. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Cloud Security Engineer

Storage Engineer

Storage Engineers design, build, and maintain storage systems. They work with other engineers, administrators, and users to ensure that storage systems are reliable, efficient, and secure. This course can help you build a foundation in streaming data processing using Google Cloud Platform. You will learn how to use Cloud Pub/Sub to process incoming streaming data, and how to apply aggregations and transformations with Cloud Dataflow. You will also learn how to store processed datasets for analysis in BigQuery or Cloud Bigtable.

See salaries and explore the career path for Storage Engineer

Reading list

We've selected three books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building Resilient Streaming Analytics Systems on GCP auf Deutsch.

Secret Colors

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Handbook on designing data-intensive applications for big data systems, and could be quite useful in providing background knowledge on building data systems.

Hadoop: The Definitive Guide

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Covers big data systems and Hadoop. It useful reference for building big data systems.

Hadoop: The Definitive Guide: Storage and Analysis...

Paperback

Hadoop: The Definitive Guide

Kindle Edition

Hadoop: The Definitive Guide

Paperback

Hadoop: The Definitive Guide

Paperback

Big Data Analytics with Java

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Covers the fundamentals of big data analytics, including data processing, machine learning, and real-time analytics, providing additional context for the course.

Big Data Analytics with Java: Data analysis,...

Paperback

$$$

Big Data Analytics with Java: Data analysis,...

Kindle Edition

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