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Este é o primeiro de uma série de três cursos sobre processamento de dados sem servidor com o Dataflow. Nele, vamos relembrar o que é o Apache Beam e qual é a relação entre ele e o Dataflow. Depois, falaremos sobre a visão do Apache Beam e os benefícios do framework de portabilidade desse modelo de programação. Com esse processo, o desenvolvedor pode usar a linguagem de programação favorita com o back-end de execução que quiser. Em seguida, mostraremos como o Dataflow permite a separação entre a computação e o armazenamento para economizar dinheiro. Além disso, você vai aprender como as ferramentas de identidade, acesso e gerenciamento interagem com os pipelines do Dataflow. Por fim, vamos ver como implementar o modelo de segurança ideal para seu caso de uso no Dataflow.
Register for this course and see more details by visiting:
OpenCourser.com/course/feo1p9/serverless
What's inside
Syllabus
Introdução
Neste módulo, apresentamos os detalhes do curso, além de um resumo rápido sobre o modelo de programação Apache Beam e o serviço gerenciado do Dataflow do Google.
Read more
Syllabus
Introdução
Neste módulo, apresentamos os detalhes do curso, além de um resumo rápido sobre o modelo de programação Apache Beam e o serviço gerenciado do Dataflow do Google.
Read more
Portabilidade do Beam
Este módulo é dividido em quatro seções: portabilidade do Beam, Runner v2, ambientes de contêiner e transformações entre linguagens.
Como separar a programação do armazenamento com o Dataflow
Neste módulo, ensinaremos como separar a programação do armazenamento com o Dataflow. Ele é dividido em quatro seções: Dataflow, serviço do Dataflow Shuffle, Dataflow Streaming Engine e programação flexível de recursos.
IAM, cotas e permissões
Neste módulo, veremos os diferentes papeis, cotas e permissões do IAM necessárias para executar o Dataflow.
Segurança
Neste módulo, veremos como implementar o modelo de segurança ideal para seu caso de uso no Dataflow.
Summary
Neste curso, começamos com um resumo sobre o que é o Apache Beam e qual é a relação dele com o Dataflow.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Este curso é o primeiro de uma série de três cursos sobre processamento de dados sem servidor com o Dataflow
O curso explora os conceitos do Apache Beam e Dataflow, ferramentas padrão na indústria de processamento de dados
Ensina como separar programação do armazenamento com o Dataflow, o que pode economizar custos
Aborda aspectos fundamentais de segurança para implementar o modelo ideal para cada caso de uso no Dataflow
O curso requer conhecimento prévio em Apache Beam e Dataflow, o que pode ser uma barreira para iniciantes
O curso não ensina versões mais recentes das ferramentas e tecnologias utilizadas
Save this course
Save Serverless Data Processing with Dataflow: Foundations em Português Brasileiro to your list so you can find it easily later:
Save
Save
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 Serverless Data Processing with Dataflow: Foundations em Português Brasileiro with these
activities:
Revise Apache Beam
Show steps
Revise the concepts of Apache Beam to strengthen your understanding of its role in Dataflow.
Browse courses on
Apache Beam
Show steps
-
Review the documentation of Apache Beam.
-
Go through a tutorial on Apache Beam.
-
Solve practice problems related to Apache Beam.
Revise Apache Beam concepts
Show steps
Understanding the fundamentals of Apache Beam will provide a solid foundation for the course.
Browse courses on
Apache Beam
Show steps
-
Review Apache Beam documentation
-
Complete Apache Beam tutorials
Review fundamental programming concepts before starting the course
Show steps
Refresher activities will strengthen your foundation and prepare you for success in this course. Start by reviewing the fundamentals.
Show steps
-
Review core programming concepts like variables, data types, and control flow.
-
Practice writing simple programs to reinforce your understanding.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore Cloud Dataflow use cases
Show steps
Examining how others utilize Cloud Dataflow will provide practical insights.
Browse courses on
Cloud Dataflow
Show steps
-
Read case studies and articles
-
Watch video tutorials
Practice transforming data with Beam
Show steps
Strengthen your understanding of how to manipulate data using Beam's transformation functions.
Browse courses on
Apache Beam
Show steps
-
Review Beam transformation concepts
-
Complete online exercises or coding challenges involving data transformations
-
Build small scripts or programs to practice applying transformations
Execute Dataflow pipelines using various programming languages
Show steps
Getting familiar with executing Dataflow pipelines using different programming languages will solidify your understanding of the Beam model.
Browse courses on
Apache Beam
Show steps
-
Choose a programming language of your choice (Java, Python, Go, or Scala).
-
Set up the necessary environment and dependencies.
-
Create a simple Dataflow pipeline using the chosen language.
-
Run and test the pipeline.
Build a data pipeline with Dataflow
Show steps
Build a real-world data pipeline to solidify your understanding of Dataflow's capabilities and apply your knowledge hands-on.
Show steps
-
Design your pipeline
-
Implement your pipeline in the preferred programming language
-
Deploy and monitor your pipeline
-
Analyze the results and make improvements
Implement a Dataflow pipeline
Show steps
Building a Dataflow pipeline will reinforce the concepts learned in the course.
Browse courses on
Data Processing
Show steps
-
Design the pipeline architecture
-
Code the pipeline using a preferred language
-
Test and deploy the pipeline
Solve Dataflow coding challenges
Show steps
Solving coding challenges will improve proficiency in applying Dataflow concepts.
Browse courses on
Big Data
Show steps
-
Find coding challenges online
-
Solve challenges using preferred language
Revise Apache Beam
Show steps
Revise the concepts of Apache Beam to strengthen your understanding of its role in Dataflow.
Browse courses on
Apache Beam
Show steps
Show steps
Show steps
- Review the documentation of Apache Beam.
- Go through a tutorial on Apache Beam.
- Solve practice problems related to Apache Beam.
Revise Apache Beam concepts
Show steps
Understanding the fundamentals of Apache Beam will provide a solid foundation for the course.
Browse courses on
Apache Beam
Show steps
Show steps
Show steps
- Review Apache Beam documentation
- Complete Apache Beam tutorials
Review fundamental programming concepts before starting the course
Show steps
Refresher activities will strengthen your foundation and prepare you for success in this course. Start by reviewing the fundamentals.
Show steps
Show steps
Show steps
- Review core programming concepts like variables, data types, and control flow.
- Practice writing simple programs to reinforce your understanding.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Explore Cloud Dataflow use cases
Show steps
Examining how others utilize Cloud Dataflow will provide practical insights.
Browse courses on
Cloud Dataflow
Show steps
Show steps
Show steps
- Read case studies and articles
- Watch video tutorials
Practice transforming data with Beam
Show steps
Strengthen your understanding of how to manipulate data using Beam's transformation functions.
Browse courses on
Apache Beam
Show steps
Show steps
Show steps
- Review Beam transformation concepts
- Complete online exercises or coding challenges involving data transformations
- Build small scripts or programs to practice applying transformations
Execute Dataflow pipelines using various programming languages
Show steps
Getting familiar with executing Dataflow pipelines using different programming languages will solidify your understanding of the Beam model.
Browse courses on
Apache Beam
Show steps
Show steps
Show steps
- Choose a programming language of your choice (Java, Python, Go, or Scala).
- Set up the necessary environment and dependencies.
- Create a simple Dataflow pipeline using the chosen language.
- Run and test the pipeline.
Build a data pipeline with Dataflow
Show steps
Build a real-world data pipeline to solidify your understanding of Dataflow's capabilities and apply your knowledge hands-on.
Show steps
Show steps
Show steps
- Design your pipeline
- Implement your pipeline in the preferred programming language
- Deploy and monitor your pipeline
- Analyze the results and make improvements
Implement a Dataflow pipeline
Show steps
Building a Dataflow pipeline will reinforce the concepts learned in the course.
Browse courses on
Data Processing
Show steps
Show steps
Show steps
- Design the pipeline architecture
- Code the pipeline using a preferred language
- Test and deploy the pipeline
Solve Dataflow coding challenges
Show steps
Solving coding challenges will improve proficiency in applying Dataflow concepts.
Browse courses on
Big Data
Show steps
Show steps
Show steps
- Find coding challenges online
- Solve challenges using preferred language
Career center
Learners who complete Serverless Data Processing with Dataflow: Foundations em Português Brasileiro will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
A Data Engineer builds, maintains, and manages data pipelines and systems. Graduates of this program will be well-prepared for this role. They will learn about programming with the Apache Beam model and how this model can be used to develop scalable and flexible data processing pipelines.
Data Scientist
Data Scientist
A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. Graduates of this program will be well-prepared for this role. They will learn about using Apache Beam to process large datasets efficiently.
Data Architect
Data Architect
A Data Architect designs, builds, and manages data architectures. Graduates of this program will be well-prepared for this role. They will learn about the principles behind building scalable, distributed systems.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. Graduates of this program may find this role to be a good fit. They will learn about the principles behind scalable, distributed computing systems.
Data Analyst
Data Analyst
A Data Analyst collects, processes, and analyzes data to help businesses make informed decisions, identify trends, and solve problems. Graduates of this program will be well-prepared for this role by learning how to build and manage data pipelines.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. Graduates of this program may find this role to be a good fit. They will learn about the principles behind building scalable, distributed systems.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and manages cloud computing solutions. Graduates of this program will be well-prepared for this role. They will learn about the principles behind building scalable, distributed systems.
Computer Scientist
Computer Scientist
A Computer Scientist conducts research in computer science and develops new computing technologies. Graduates of this program will be well-prepared for this role. They will learn about the principles behind building scalable, distributed systems.
DevOps Engineer
DevOps Engineer
A DevOps Engineer works with software developers and system administrators to ensure that software is built, tested, and deployed efficiently. Graduates of this program may find this role to be a good fit. They will learn about the principles behind building scalable, distributed systems.
IT Manager
IT Manager
An IT Manager plans, coordinates, and directs the implementation of information technology systems. Graduates of this program may find this role to be a good fit. They will learn about the principles behind building scalable, distributed systems.
Security Engineer
Security Engineer
A Security Engineer designs, builds, and manages security systems. Graduates of this program will be well-prepared for this role. They will learn about the principles behind building secure, distributed systems.
Network Engineer
Network Engineer
A Network Engineer designs, builds, and manages networks. Graduates of this program may find this role to be a good fit. They will learn about the principles behind building scalable, distributed systems.
Systems Engineer
Systems Engineer
A Systems Engineer designs, builds, and manages computer systems. Graduates of this program will be well-prepared for this role. They will learn about the principles behind building scalable, distributed systems.
Big Data Engineer
Big Data Engineer
A Big Data Engineer designs, builds, and manages big data systems. Graduates of this program will be well-prepared for this role. They will learn about the principles behind building scalable, distributed systems.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and develops solutions to improve efficiency and effectiveness. Graduates of this program may find this role to be a good fit. They will learn about the principles behind building scalable, distributed systems.
For more career information including salaries, visit:
OpenCourser.com/course/feo1p9/serverless
Reading list
We've selected 13 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
Serverless Data Processing with Dataflow: Foundations em Português Brasileiro.
Save
Provides a comprehensive overview of generative adversarial networks, including the fundamental concepts, algorithms, and applications.
Save
Comprehensive reference on deep learning, covering a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Save
Provides a comprehensive overview of computer vision, covering a wide range of topics, including image processing, object recognition, and scene understanding.
Provides a comprehensive overview of reinforcement learning, including the fundamental concepts, algorithms, and applications.
Comprehensive reference on database systems, covering a wide range of topics, including data models, database design, query processing, and transaction management.
For a deeper dive into Spark, this book serves as a comprehensive guide to Spark, providing in-depth coverage of Spark's core concepts, including RDDs, transformations, and actions.
Save
Provides a comprehensive overview of data mining techniques, including data preprocessing, data mining algorithms, and data visualization.
Provides a practical guide to natural language processing, covering a wide range of topics, including text preprocessing, text classification, and machine translation.
Save
Provides a comprehensive overview of data-intensive architectures and design patterns. It covers topics such as data modeling, data storage and retrieval, stream processing, and data quality. It helps in understanding the broader context of data processing and how Dataflow fits into the overall landscape
Covers the fundamentals of data pipelines, including design patterns, data quality management, and monitoring. It provides a vendor-neutral perspective on data pipelines and helps in understanding the broader concepts applicable to Dataflow
As the course covers Hadoop in detail, this book serves as an advanced reference on Hadoop, providing comprehensive coverage of the Hadoop ecosystem, including HDFS, MapReduce, and Hive.
Explores stream processing using Apache Flink. Although not directly related to Dataflow, Flink is another popular open-source framework for stream processing. Reading this book can provide insights into alternative approaches and concepts in real-time data processing
Provides a business-oriented view of data analytics. It covers topics such as data exploration, data visualization, and storytelling. It helps in understanding the importance of data processing for decision-making and business value
For more information about how these books relate to this course, visit:
OpenCourser.com/course/feo1p9/serverless
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Effort
3 weeks of study, 6-8 hours/week
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Português
Transcript
English
This course belongs to a
collection
called
Serverless Data Processing Dataflow em Português Brasileiro. It's comprised of three courses:
- Serverless Data Processing with Dataflow: Develop Pipelines em Português Brasileiro
- Serverless Data Processing with Dataflow: Foundations em Português Brasileiro (viewing)
- Serverless Data Processing with Dataflow: Operations em Português Brasileiro
Good to know
Este curso é o primeiro de uma série de três cursos sobre processamento de dados sem servidor com o Dataflow
O curso explora os conceitos do Apache Beam e Dataflow, ferramentas padrão na indústria de processamento de dados
Ensina como separar programação do armazenamento com o Dataflow, o que pode economizar custos
Aborda aspectos fundamentais de segurança para implementar o modelo ideal para cada caso de uso no Dataflow
O curso requer conhecimento prévio em Apache Beam e Dataflow, o que pode ser uma barreira para iniciantes
O curso não ensina versões mais recentes das ferramentas e tecnologias utilizadas
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