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Google Cloud Training
Los dos componentes clave de cualquier canalización de datos son los data lakes y los almacenes de datos. En este curso, se destacan los casos de uso de cada tipo de almacenamiento y se analizan en profundidad las soluciones de data lakes y almacenes disponibles en Google Cloud con detalles técnicos. Además, en este curso, se describen el rol del ingeniero en datos, los beneficios de las canalizaciones de datos exitosas para las operaciones comerciales y por qué la ingeniería de datos debe realizarse en un entorno de nube.Este el primer curso de la serie Data Engineering on Google Cloud. Después de completar este curso, inscríbase en Building Batch Data Pipelines on Google Cloud.
Register for this course and see more details by visiting:
OpenCourser.com/course/83lcjy/modernizing
What's inside
Syllabus
Introducción
Este módulo es la introducción a la serie de cursos Data Engineering on Google Cloud y al curso Modernizing Data Lake and Data Warehouses with Google Cloud.
Read more
Syllabus
Introducción
Este módulo es la introducción a la serie de cursos Data Engineering on Google Cloud y al curso Modernizing Data Lake and Data Warehouses with Google Cloud.
Read more
Introducción a la ingeniería de datos
En este módulo, se describe el rol del ingeniero de datos y se justifica por qué la ingeniería de datos debe realizarse en la nube.
Cree un data lake
En este módulo, se describe qué es data lake y cómo utilizar Cloud Storage como data lake en Google Cloud.
Cree un almacén de datos
En este módulo, hablamos sobre BigQuery como opción de almacenamiento de datos en Google Cloud.
Resumen
Resumen de los puntos de aprendizaje clave
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Perfecta para ingenieros de datos que buscan modernizar sus almacenes de datos y lagos de datos utilizando Google Cloud
Adecuada para estudiantes que buscan una base sólida en la ingeniería de datos utilizando Google Cloud
Impartida por Google Cloud Training, reconocidos por su experiencia en la ingeniería de datos en la nube
Cubre los aspectos técnicos de las soluciones de lagos de datos y almacenes de datos disponibles en Google Cloud
Requiere conocimientos previos en ingeniería de datos
No proporciona experiencia práctica en la creación de canalizaciones de datos reales
Save this course
Save Modernizing Data Lakes and Data Warehouses with GCP en Español to your list so you can find it easily later:
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Reviews summary
Modernizing data lakes and data warehouses in gcp
This course is a well-received introduction to the role of data engineers in creating data lakes and data warehouses using Google Cloud Platform (GCP). It is well-paced, includes hands-on labs, and provides helpful examples for each topic. While some reviewers had trouble with the labs or accessing certain resources, overall the course is comprehensive and provides a strong foundation in the subject matter.
Concepts are explained clearly and concretely.
"Excelentes lo concreto de las explicaciones, y todo el contenido"
Includes hands-on labs with helpful examples.
"Very nice explanation, examples and labs."
"love the last section where we could put on practice the knowledge obtained"
Labs may be outdated and cause errors.
"Lo más importante es el tema de los errores en los Labs que, evidentemente están desactualizados respecto a la plataforma."
Some resources mentioned in videos are not available.
"Además, hay links y recursos que hablan en los videos, que dicen que dejan disponibles, pero no están en ningún lado."
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 Modernizing Data Lakes and Data Warehouses with GCP en Español with these
activities:
Assemble a resource toolkit
Show steps
Build a collection of essential resources, including tutorials, documentation, and blog posts, to aid your learning and ongoing reference.
Show steps
-
Identify and gather relevant resources from reputable sources
-
Organize the resources into a central location for easy access
Review relational databases
Show steps
Review the basics of relational databases to lay a solid foundation for understanding the principles of data engineering.
Show steps
-
Revisit concepts of data modeling and normalization
-
Practice creating tables, indexes, and constraints
-
Refresh your knowledge on SQL queries
Explore BigQuery tutorials
Show steps
Deepen your understanding of BigQuery by working through interactive tutorials to gain hands-on experience in data warehousing and SQL.
Browse courses on
BigQuery
Show steps
-
Complete the 'BigQuery for Beginners' tutorial
-
Follow the 'Analyzing Data with SQL' tutorial
-
Explore advanced BigQuery features through additional tutorials
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a data engineering study group
Show steps
Engage in peer discussions to expand your understanding and knowledge of data engineering concepts and best practices.
Browse courses on
Data Engineering
Show steps
-
Join a data engineering study group online or in-person
-
Participate actively in group discussions and knowledge-sharing sessions
Attend a BigQuery workshop
Show steps
Gain hands-on experience and in-depth knowledge of BigQuery by participating in a dedicated workshop led by experts.
Browse courses on
BigQuery
Show steps
-
Register for a BigQuery workshop in your area or online
-
Actively engage in workshop activities and ask questions
Build a data lake prototype
Show steps
Apply your understanding of data lakes by constructing a basic data lake prototype using Cloud Storage and BigQuery to manage and analyze data.
Browse courses on
Data Lakes
Show steps
-
Create a Cloud Storage bucket
-
Set up a BigQuery dataset
-
Load data into Cloud Storage and BigQuery
-
Explore and analyze the data using SQL
Contribute to open-source data engineering projects
Show steps
Gain practical experience and make valuable contributions to the data engineering community by participating in open-source projects.
Browse courses on
Data Engineering
Show steps
-
Identify open-source data engineering projects seeking contributors
-
Review project documentation and select a suitable task
-
Contribute code, documentation, or bug fixes to the project
Participate in a data engineering hackathon
Show steps
Challenge yourself by applying your data engineering skills in a competitive environment to solve real-world data-related problems.
Browse courses on
Data Engineering
Show steps
-
Identify and register for an appropriate data engineering hackathon
-
Collaborate with a team or work individually to develop a solution
-
Present your solution to a panel of judges
Assemble a resource toolkit
Show steps
Build a collection of essential resources, including tutorials, documentation, and blog posts, to aid your learning and ongoing reference.
Show steps
Show steps
Show steps
- Identify and gather relevant resources from reputable sources
- Organize the resources into a central location for easy access
Review relational databases
Show steps
Review the basics of relational databases to lay a solid foundation for understanding the principles of data engineering.
Show steps
Show steps
Show steps
- Revisit concepts of data modeling and normalization
- Practice creating tables, indexes, and constraints
- Refresh your knowledge on SQL queries
Explore BigQuery tutorials
Show steps
Deepen your understanding of BigQuery by working through interactive tutorials to gain hands-on experience in data warehousing and SQL.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Complete the 'BigQuery for Beginners' tutorial
- Follow the 'Analyzing Data with SQL' tutorial
- Explore advanced BigQuery features through additional tutorials
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a data engineering study group
Show steps
Engage in peer discussions to expand your understanding and knowledge of data engineering concepts and best practices.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Join a data engineering study group online or in-person
- Participate actively in group discussions and knowledge-sharing sessions
Attend a BigQuery workshop
Show steps
Gain hands-on experience and in-depth knowledge of BigQuery by participating in a dedicated workshop led by experts.
Browse courses on
BigQuery
Show steps
Show steps
Show steps
- Register for a BigQuery workshop in your area or online
- Actively engage in workshop activities and ask questions
Build a data lake prototype
Show steps
Apply your understanding of data lakes by constructing a basic data lake prototype using Cloud Storage and BigQuery to manage and analyze data.
Browse courses on
Data Lakes
Show steps
Show steps
Show steps
- Create a Cloud Storage bucket
- Set up a BigQuery dataset
- Load data into Cloud Storage and BigQuery
- Explore and analyze the data using SQL
Contribute to open-source data engineering projects
Show steps
Gain practical experience and make valuable contributions to the data engineering community by participating in open-source projects.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Identify open-source data engineering projects seeking contributors
- Review project documentation and select a suitable task
- Contribute code, documentation, or bug fixes to the project
Participate in a data engineering hackathon
Show steps
Challenge yourself by applying your data engineering skills in a competitive environment to solve real-world data-related problems.
Browse courses on
Data Engineering
Show steps
Show steps
Show steps
- Identify and register for an appropriate data engineering hackathon
- Collaborate with a team or work individually to develop a solution
- Present your solution to a panel of judges
Career center
Learners who complete Modernizing Data Lakes and Data Warehouses with GCP en Español will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines that move data between different systems. They also develop and implement data quality processes to ensure that data is accurate and reliable. This course provides Data Engineers with a deep understanding of data lake and data warehouse technologies, which are essential for building and maintaining data pipelines. By completing this course, Data Engineers will be better equipped to design and build scalable and efficient data pipelines.
Data Architect
Data Architect
Data Architects design and implement data management solutions. They work with businesses to determine their data management needs and then design and implement solutions that meet those needs. This course helps Data Architects build a foundation in data lake and data warehouse technologies, which are essential for building and maintaining data management solutions. By completing this course, Data Architects will be better equipped to design and implement scalable and efficient data lakes and data warehouses.
Data Warehouse Architect
Data Warehouse Architect
Data Warehouse Architects design and implement data warehouses. They work with businesses to determine their data warehousing needs and then design and implement solutions that meet those needs. This course helps Data Warehouse Architects build a foundation in data lake and data warehouse technologies, which are essential for building and maintaining data warehouses. By completing this course, Data Warehouse Architects will be better equipped to design and implement scalable and efficient data warehouses.
Data Analyst
Data Analyst
Data Analysts provide information and insights that help businesses make informed decisions. They use their understanding of data to identify trends, patterns, and anomalies. This course helps Data Analysts build a foundation in data lake and data warehouse technologies, which are essential for storing and managing large volumes of data. By completing this course, Data Analysts will be better equipped to gather, clean, and analyze data to help their organizations make better decisions.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement data governance policies and procedures. They work with businesses to determine their data governance needs and then develop and implement solutions that meet those needs. This course helps Data Governance Analysts build a foundation in data lake and data warehouse technologies, which are essential for storing and managing large volumes of data. By completing this course, Data Governance Analysts will be better equipped to develop and implement data governance policies and procedures that involve data lakes and data warehouses.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to identify trends and patterns that can help businesses make better decisions. They develop and implement reporting and visualization tools to help businesses understand their data. This course helps Business Intelligence Analysts build a foundation in data lake and data warehouse technologies, which are essential for storing and managing large volumes of data. By completing this course, Business Intelligence Analysts will be better equipped to gather, clean, and analyze data to develop insights that can help their businesses make better decisions.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models. They work with businesses to determine their machine learning needs and then design and implement solutions that meet those needs. This course helps Machine Learning Engineers build a foundation in data lake and data warehouse technologies, which are essential for storing and managing large volumes of data. By completing this course, Machine Learning Engineers will be better equipped to gather, clean, and analyze data to develop and implement machine learning models.
Data Scientist
Data Scientist
Data Scientists use statistical and machine learning techniques to extract insights from data. They develop and implement predictive models to help businesses make informed decisions. This course helps Data Scientists build a foundation in data lake and data warehouse technologies, which are essential for storing and managing large volumes of data. By completing this course, Data Scientists will be better equipped to gather, clean, and analyze data to develop predictive models.
Database Administrator
Database Administrator
Database Administrators maintain and optimize databases to ensure that they are performing optimally. They also implement security measures to protect data from unauthorized access. This course helps Database Administrators build a foundation in data lake and data warehouse technologies, which are becoming increasingly popular for storing and managing large volumes of data. By completing this course, Database Administrators will be better equipped to manage and optimize data lakes and data warehouses.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. They work with businesses to determine their cloud computing needs and then design and implement solutions that meet those needs. This course helps Cloud Architects build a foundation in data lake and data warehouse technologies, which are essential for building and maintaining cloud computing solutions. By completing this course, Cloud Architects will be better equipped to design and implement scalable and efficient data lakes and data warehouses in the cloud.
Project Manager
Project Manager
Project Managers lead and manage projects. They work with businesses to determine their project needs and then develop and implement plans to meet those needs. This course helps Project Managers build a foundation in data lake and data warehouse technologies, which are becoming increasingly popular for storing and managing large volumes of data. By completing this course, Project Managers will be better equipped to lead and manage projects that involve data lakes and data warehouses.
Technical Program Manager
Technical Program Manager
Technical Program Managers lead and manage technical projects. They work with businesses to determine their project needs and then develop and implement plans to meet those needs. This course helps Technical Program Managers build a foundation in data lake and data warehouse technologies, which are becoming increasingly popular for storing and managing large volumes of data. By completing this course, Technical Program Managers will be better equipped to lead and manage technical projects that involve data lakes and data warehouses.
Product Manager
Product Manager
Product Managers define and manage the development of products. They work with businesses to determine their product needs and then develop and implement plans to meet those needs. This course helps Product Managers build a foundation in data lake and data warehouse technologies, which are becoming increasingly popular for storing and managing large volumes of data. By completing this course, Product Managers will be better equipped to define and manage products that involve data lakes and data warehouses.
Business Analyst
Business Analyst
Business Analysts define and manage the development of business processes. They work with businesses to determine their business needs and then develop and implement plans to meet those needs. This course helps Business Analysts build a foundation in data lake and data warehouse technologies, which are becoming increasingly popular for storing and managing large volumes of data. By completing this course, Business Analysts will be better equipped to define and manage business processes that involve data lakes and data warehouses.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with businesses to determine their software needs and then design and implement solutions that meet those needs. This course helps Software Engineers build a foundation in data lake and data warehouse technologies, which are becoming increasingly popular for storing and managing large volumes of data. By completing this course, Software Engineers will be better equipped to design and implement scalable and efficient data lakes and data warehouses.
For more career information including salaries, visit:
OpenCourser.com/course/83lcjy/modernizing
Reading list
We've selected seven 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
Modernizing Data Lakes and Data Warehouses with GCP en Español.
Is considered a classic in the field of data warehousing. It provides a comprehensive guide to dimensional modeling, a fundamental concept in data warehousing design.
Foundational text on data-intensive applications. It covers key principles of data modeling, data storage, and data management, making it a valuable resource for those seeking to understand the underlying concepts of modern data systems.
Introduces data-oriented architecture as a design paradigm for modern data systems. It covers key concepts and patterns for data integration and management.
Is considered a foundational text on Hadoop, a widely used framework for big data processing. It provides a comprehensive guide to Hadoop's architecture, components, and programming models.
Is considered a foundational text on Apache Spark, a popular framework for big data processing. It provides a comprehensive guide to Spark's architecture, components, and programming models.
Provides a comprehensive introduction to data science. It covers the fundamentals of data analysis, machine learning, and data visualization, making it a useful resource for those seeking to understand the broader context of data engineering.
Provides a comprehensive overview of big data analytics. It covers the fundamentals of data exploration, data mining, and data visualization, making it a useful resource for those seeking to understand the process of extracting insights from large datasets.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/83lcjy/modernizing
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Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Español
Transcript
English
Good to know
Perfecta para ingenieros de datos que buscan modernizar sus almacenes de datos y lagos de datos utilizando Google Cloud
Adecuada para estudiantes que buscan una base sólida en la ingeniería de datos utilizando Google Cloud
Impartida por Google Cloud Training, reconocidos por su experiencia en la ingeniería de datos en la nube
Cubre los aspectos técnicos de las soluciones de lagos de datos y almacenes de datos disponibles en Google Cloud
Requiere conocimientos previos en ingeniería de datos
No proporciona experiencia práctica en la creación de canalizaciones de datos reales
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