Building Resilient Streaming Systems on Google Cloud Platform en Español from Coursera

Este curso acelerado a pedido de una semana está basado en Google Cloud Platform Big Data and Machine Learning Fundamentals. Mediante una serie de clases por video, demostraciones y labs prácticos, aprenderá a compilar canalizaciones de datos de transmisión con Google Cloud Pub/Sub y Dataflow para poder tomar decisiones en tiempo real. Además, aprenderá a compilar paneles a fin de procesar resultados personalizados para distintos públicos interesados. Requisitos previos: • Haber completado el curso Google Cloud Platform Big Data and Machine Learning Fundamentals (o contar con experiencia equivalente) • Conocimientos de Java Objetivos: • Comprender casos prácticos de estadísticas de transmisiones en tiempo real • Usar el servicio de mensajería asíncrona de Google Cloud Pub/Sub para administrar eventos de datos • Escribir canalizaciones de transmisión y ejecutar transformaciones cuando sea necesario • Familiarizarse con ambos lados de una canalización de transmisión: la producción y el consumo • Interoperar Dataflow, BigQuery y Cloud Pub/Sub para realizar transmisiones y análisis en tiempo real

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

You will apply concepts from Google Cloud Platform Big Data and Machine Learning Fundamentals

Google Cloud Training is known for the quality of their instruction

Course provides an advanced training in the field of Big Data statistics and technology.

Reviews summary

Highly rated course on gcp streaming systems

This course is highly rated by students and is considered a great resource for learning about building resilient streaming systems on Google Cloud Platform. Students particularly appreciate the detailed explanations of GCP platform and well-defined practice exercises.

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 Systems on Google Cloud Platform en Español with these activities:

Review Java

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Refresh your Java skills before class to ensure you can fully follow along.

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Review Java fundamentals
Practice writing simple Java programs

Study Group

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Engage with classmates to discuss concepts and reinforce your understanding through peer-to-peer learning.

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Form a study group with your fellow students
Meet regularly to go over course material and discuss concepts

Dataflow Transformations

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Practice writing Dataflow transformations to enhance your hands-on skills.

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Find a dataset to practice with
Write Dataflow transformations to process the data

One other activity

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Data Visualization

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Create a data visualization using BigQuery and Data Studio to demonstrate your understanding of the real-time data analysis process.

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Choose a data source
Design your data visualization
Create your visualization using BigQuery and Data Studio

Career center

Learners who complete Building Resilient Streaming Systems on Google Cloud Platform en Español will develop knowledge and skills that may be useful to these careers:

Data Engineer

Data Engineers design, build, test, and maintain data management systems within an organization. These systems include the capture, storage, organization, analysis, and management of data. Having the skills to build resilient streaming systems, as taught in this course, is a core responsibility of a Data Engineer. This course would provide the foundation to build such systems on Google Cloud Platform and would lead to career success as a Data Engineer.

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Data Architect

Data Architects design, build, manage, and maintain an organization's data ecosystem. This includes the development of data management strategies, policies, and standards. The ability to build resilient streaming systems, as taught in this course, would enable one to design data ecosystems that are scalable, reliable, and fault-tolerant. This course would provide the foundation for success as a Data Architect.

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Data Scientist

Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. This course covers the skills needed to build streaming data pipelines using Google Cloud Pub/Sub and Dataflow, which are essential for real-time data analysis. This course would be highly beneficial for aspiring Data Scientists, especially those interested in working with streaming data.

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Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning systems. These systems can be used for a variety of tasks, such as image recognition, natural language processing, and predictive analytics. The ability to build streaming machine learning pipelines, as taught in this course, is becoming increasingly important as real-time data analysis becomes more prevalent. This course would provide the foundation for success as a Machine Learning Engineer, especially for those interested in working with streaming data.

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Big Data Engineer

Big Data Engineers design, build, and maintain systems for processing and analyzing large datasets. These systems typically involve the use of distributed computing technologies, such as Hadoop and Spark. The ability to build resilient streaming data pipelines, as taught in this course, is essential for Big Data Engineers. This course would provide the foundation for success as a Big Data Engineer, especially for those interested in working with streaming data.

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Cloud Architect

Cloud Architects design, build, and maintain cloud computing systems. These systems typically involve the use of multiple cloud services, such as those provided by Google Cloud Platform. The ability to build resilient streaming data pipelines, as taught in this course, is becoming increasingly important as more organizations adopt cloud computing. This course would provide the foundation for success as a Cloud Architect, especially for those interested in working with streaming data.

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DevOps Engineer

DevOps Engineers are responsible for bridging the gap between development and operations teams. They work to ensure that software is developed and deployed quickly and reliably. The ability to build resilient streaming data pipelines, as taught in this course, is becoming increasingly important as organizations adopt continuous delivery and DevOps practices. This course would provide the foundation for success as a DevOps Engineer, especially for those interested in working with streaming data.

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Software Engineer

Software Engineers design, develop, and maintain software systems. These systems can be used for a variety of purposes, such as business process automation, data analysis, and web development. The ability to build resilient streaming data pipelines, as taught in this course, is becoming increasingly important as more organizations adopt real-time data processing. This course would provide the foundation for success as a Software Engineer, especially for those interested in working with streaming data.

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Data Analyst

Data Analysts collect, clean, and analyze data to help organizations make informed decisions. The ability to build resilient streaming data pipelines, as taught in this course, is becoming increasingly important as more organizations adopt real-time data analysis. This course would provide the foundation for success as a Data Analyst, especially for those interested in working with streaming data.

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Business Analyst

Business Analysts work with stakeholders to understand their business needs and develop solutions to meet those needs. The ability to build resilient streaming data pipelines, as taught in this course, is becoming increasingly important as more organizations adopt real-time data analysis. This course would provide the foundation for success as a Business Analyst, especially for those interested in working with streaming data.

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Product Manager

Product Managers are responsible for defining, developing, and launching new products. The ability to build resilient streaming data pipelines, as taught in this course, is becoming increasingly important as more organizations adopt real-time data analysis. This course would provide the foundation for success as a Product Manager, especially for those interested in working with streaming data.

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Project Manager

Project Managers are responsible for planning, executing, and completing projects. The ability to build resilient streaming data pipelines, as taught in this course, may be useful for Project Managers who are working on projects that involve real-time data processing.

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Database Administrator

Database Administrators are responsible for managing and maintaining databases. The ability to build resilient streaming data pipelines, as taught in this course, may be useful for Database Administrators who are working with databases that are used for real-time data processing.

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Data Visualization Analyst

Data Visualization Analysts are responsible for creating visualizations that help organizations understand their data. The ability to build resilient streaming data pipelines, as taught in this course, may be useful for Data Visualization Analysts who are working with real-time data.

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QA Tester

QA Testers are responsible for testing software to ensure that it meets requirements. The ability to build resilient streaming data pipelines, as taught in this course, may be useful for QA Testers who are working with software that processes real-time data.

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