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Google Cloud Training
Las canalizaciones de datos suelen realizarse según uno de los siguientes paradigmas: extracción y carga (EL); extracción, carga y transformación (ELT), o extracción, transformación y carga (ETL). En este curso, abordaremos qué paradigma se debe utilizar para los datos por lotes y cuándo corresponde usarlo. Además, veremos varias tecnologías de Google Cloud para la transformación de datos, incluidos BigQuery, la ejecución de Spark en Dataproc, gráficos de canalización en Cloud Data Fusion y procesamiento de datos sin servidores en Dataflow. Los alumnos obtendrán experiencia práctica en la compilación de componentes de canalizaciones de datos en Google Cloud con Qwiklabs.
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What's inside
Syllabus
Introducción
En este módulo, presentamos el curso y el temario
Introducción a Building Batch Data Pipelines
En este módulo, se revisan los diferentes métodos de carga de datos: EL, ELT y ETL, y cuándo corresponde usarlos
Read more
Syllabus
Introducción
En este módulo, presentamos el curso y el temario
Introducción a Building Batch Data Pipelines
En este módulo, se revisan los diferentes métodos de carga de datos: EL, ELT y ETL, y cuándo corresponde usarlos
Read more
Ejecución de Spark en Dataproc
En este módulo, se muestra cómo ejecutar Hadoop en Dataproc, usar Cloud Storage y optimizar sus trabajos de Dataproc.
Procesamiento de datos sin servidor con Dataflow
En este módulo, se aborda el uso de Dataflow para compilar sus canalizaciones de procesamiento de datos
Administración de canalizaciones de datos con Cloud Data Fusion y Cloud Composer
En este módulo, se muestra como administrar canalizaciones de datos con Cloud Data Fusion y Cloud Composer
Resumen del curso
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
El curso cubre los paradigmas de las canalizaciones de datos: extracción y carga (EL); extracción, carga y transformación (ELT); y extracción, transformación y carga (ETL)
Proporciona experiencia práctica en la compilación de componentes de canalizaciones de datos con Qwiklabs
Incluye tecnologías de Google Cloud para la transformación de datos, como BigQuery, Spark en Dataproc, Cloud Data Fusion y Dataflow
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Reviews summary
Batch pipelines on gcp in spanish
Building Batch Data Pipelines on GCP en Español teaches students how to build batch data pipelines on Google Cloud Platform using various technologies. The course covers the benefits and drawbacks of three data pipeline paradigms, and also provides hands-on experience with Qwiklabs. While most reviews are positive, some students report difficulties with the labs. Overall, students recommend this course for those who want to learn about data pipelines on GCP.
Course covers EL, ELT, and ETL
Hands-on practice with Qwiklabs
"...las parcticas son muy utiles"
Some students reported issues
"se me presentaron varios problemas con los laboratorios"
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 Batch Data Pipelines on GCP en Español with these
activities:
Crear proyectos de programación personales
Show steps
Trabajar en proyectos de programación personales permitirá aplicar los conceptos avanzados aprendidos en este curso y desarrollar habilidades prácticas.
Show steps
-
Identificar una idea para un proyecto que desafíe las habilidades.
-
Diseñar y planificar la arquitectura del proyecto.
-
Implementar el proyecto y probarlo a fondo.
-
Documentar el proyecto y compartirlo con otros.
Show all one activities
Crear proyectos de programación personales
Show steps
Trabajar en proyectos de programación personales permitirá aplicar los conceptos avanzados aprendidos en este curso y desarrollar habilidades prácticas.
Show steps
Show steps
Show steps
- Identificar una idea para un proyecto que desafíe las habilidades.
- Diseñar y planificar la arquitectura del proyecto.
- Implementar el proyecto y probarlo a fondo.
- Documentar el proyecto y compartirlo con otros.
Show all one activities
Career center
Learners who complete Building Batch Data Pipelines on GCP en Español will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts gather, analyze, and interpret data in order to uncover trends that can be used to help organizations improve their operations. Many Data Analysts work with Big Data, or vast amounts of complex data, and use statistical methods, programming, and analytical software to analyze data. This course may be very useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, all of which are used by a Data Analyst.
Data Integration Engineer
Data Integration Engineer
Data Integration Engineers design, develop, and maintain data integration solutions. They work with data analysts and other stakeholders to identify data needs, and then design and implement data integration solutions. This course may be very useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are essential skills for Data Integration Engineers.
Data Architect
Data Architect
Data Architects design, build, and maintain data infrastructure. They work with data analysts and other stakeholders to identify data needs, and then design and implement data infrastructure solutions. This course may be very useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are essential skills for Data Architects.
Data Warehouse Manager
Data Warehouse Manager
Data Warehouse Managers are responsible for the design, implementation, and maintenance of data warehouses. They work with data analysts and other stakeholders to identify data needs, and then design and implement data warehouse solutions. This course may be very useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, and how to apply them to maintain data warehouses.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. They analyze data to uncover trends, patterns, and anomalies, and use this information to help organizations make better decisions. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which can help Data Scientists build and enhance their data analysis skills.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts help organizations make better decisions by providing them with data-driven insights. They analyze data to identify trends, patterns, and anomalies, and then use this information to help organizations make better decisions. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are essential skills for Business Intelligence Analysts.
Data Scientist Manager
Data Scientist Manager
Data Scientist Managers lead teams of data scientists and are responsible for the overall success of data science projects. They work with stakeholders to identify business problems that can be solved with data science, and then lead teams of data scientists to develop and deploy data science solutions. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are essential skills for Data Scientist Managers.
Information Security Analyst
Information Security Analyst
Information Security Analysts design and implement security measures to protect an organization's computer networks and systems. Their goal is to prevent unauthorized access, use, disclosure, disruption, modification, or destruction of an organization's information assets. This course may be useful for your career growth, as it provides an overview of data ETL, data processing, and data pipelines, which can be helpful for understanding data security and protection.
Data Engineer
Data Engineer
A Data Engineer is a software developer who specializes in designing, constructing and maintaining the infrastructure of data pipelines. Data Engineers develop automated techniques for extracting, transforming, and loading (ETL) data, and then configuring and managing the systems that process this data. They usually work as part of a team which includes Data Scientists, Database Administrators, and Data Analysts. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are essential skills for a Data Engineer.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work with data scientists and other stakeholders to identify business problems that can be solved with machine learning, and then design and develop machine learning solutions. This course may be useful for your career growth, as it provides an overview of data ETL, data processing, and data pipelines, which are essential skills for Machine Learning Engineers.
Data Governance Specialist
Data Governance Specialist
Data Governance Specialists develop and implement data governance policies and procedures. They work with stakeholders to identify data assets and risks, and then develop and implement data governance policies and procedures to protect these assets and risks. This course may be useful for your career growth, as it provides an overview of data ETL, data processing, and data pipelines, which are essential skills for Data Governance Specialists.
Chief Data Officer
Chief Data Officer
Chief Data Officers are responsible for the overall data strategy and governance of an organization. They work with stakeholders to identify business problems that can be solved with data, and then develop and implement data strategies and governance policies. This course may be useful for your career growth, as it provides an overview of data ETL, data processing, and data pipelines, which are essential skills for Chief Data Officers.
Database Administrator
Database Administrator
Database Administrators are responsible for the installation, configuration, maintenance, and performance monitoring of database management systems. They may also provide technical support to database users, and design and implement database security measures. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are essential skills for managing databases.
Software Engineer
Software Engineer
Software Engineers design, develop, maintain, test, and deploy software applications. They may work on a variety of projects, from small personal apps to large enterprise systems. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which are important skills for designing and developing software applications.
Web Developer
Web Developer
Web Developers design and create websites. They may work on a variety of projects, from small personal websites to large e-commerce sites. This course may be useful for your career growth, as it covers concepts such as data ETL, data processing, and data pipelines, which can be helpful for understanding how to manage and process data on the web.
For more career information including salaries, visit:
OpenCourser.com/course/h098pm/building
Reading list
We've selected six 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 Batch Data Pipelines on GCP en Español.
Provides comprehensive coverage of data engineering with Python, including data ingestion, transformation, and analysis techniques. It serves as a valuable reference for understanding the broader context of data pipelines and the practical implementation of these concepts.
This comprehensive guide to Apache Spark provides in-depth coverage of the technology used in the course. It valuable reference for understanding the underlying concepts and implementing Spark-based data pipelines.
Focuses on building automated data pipelines for data science and machine learning workflows. It provides practical guidance on implementing and managing pipelines for data preparation, model training, and evaluation.
Provides a comprehensive overview of designing and building data-intensive applications. It covers topics such as data modeling, data storage, and data processing, offering a broader perspective on the concepts covered in the course.
Save
Covers the fundamentals of ETL (Extract, Transform, Load) processes using Python. It provides practical examples and guidance on implementing ETL pipelines, complementing the course's coverage of EL, ELT, and ETL paradigms.
Save
Este libro clásico proporciona una base sólida en los principios y prácticas de la integración de datos. Ofrece una perspectiva histórica y conceptual que complementa el enfoque práctico del curso.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/h098pm/building
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Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Español
Transcript
English
Good to know
El curso cubre los paradigmas de las canalizaciones de datos: extracción y carga (EL); extracción, carga y transformación (ELT); y extracción, transformación y carga (ETL)
Proporciona experiencia práctica en la compilación de componentes de canalizaciones de datos con Qwiklabs
Incluye tecnologías de Google Cloud para la transformación de datos, como BigQuery, Spark en Dataproc, Cloud Data Fusion y Dataflow
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