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Google Cloud Training

Os dois principais componentes de um pipeline de dados são data lakes e warehouses. Neste curso, destacamos os casos de uso para cada tipo de armazenamento e as soluções de data lake e warehouse disponíveis no Google Cloud de forma detalhada e técnica. Além disso, também descrevemos o papel de um engenheiro de dados, os benefícios de um pipeline de dados funcional para operações comerciais e analisamos por que a engenharia de dados deve ser feita em um ambiente de nuvem.

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Os dois principais componentes de um pipeline de dados são data lakes e warehouses. Neste curso, destacamos os casos de uso para cada tipo de armazenamento e as soluções de data lake e warehouse disponíveis no Google Cloud de forma detalhada e técnica. Além disso, também descrevemos o papel de um engenheiro de dados, os benefícios de um pipeline de dados funcional para operações comerciais e analisamos por que a engenharia de dados deve ser feita em um ambiente de nuvem.

Este é o primeiro curso da série "Data Engineering on Google Cloud". Após a conclusão, recomendamos que você comece o curso "Building Batch Data Pipelines on Google Cloud".

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What's inside

Syllabus

Introdução
Este módulo é o primeiro da série "Data Engineering on Google Cloud" e do curso "Modernizing Data Lakes and Data Warehouses with Google Cloud".
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Ensina técnicas avançadas de engenharia de dados que são fundamentais para profissionais da área de TI
Aborda tópicos essenciais, como data lakes e data warehouses, que são amplamente utilizados em cenários de big data
Oferece exemplos práticos e demonstrações usando Google Cloud, que é uma plataforma líder na indústria
Fornece uma base sólida para profissionais que buscam aprimorar suas habilidades em engenharia de dados
Requer conhecimento prévio em conceitos de engenharia de dados e tecnologias de nuvem

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Reviews summary

Fundamentos de data engineering com gcp

De acordo com os alunos, este curso é uma excelente introdução para engenharia de dados no Google Cloud, especialmente para quem busca uma base sólida em data lakes e data warehouses. Muitos destacam a clareza na explicação do Cloud Storage e BigQuery, bem como a importância dos laboratórios práticos para fixar o aprendizado. Embora seja elogiado como um ótimo ponto de partida para iniciantes, alguns consideram o conteúdo básico demais para quem já possui experiência na área.
Excelente para quem está começando em engenharia de dados no Google Cloud.
"Para quem está começando com engenharia de dados no Google Cloud, este curso é um ótimo ponto de partida."
"Conteúdo relevante e atualizado sobre GCP. A explicação sobre data lakes e warehouses é muito boa."
"Recomendo a todos que querem começar a entrar no mundo dos dados e do GCP."
Apresenta conteúdo com didática excelente e laboratórios práticos úteis.
"Muito bom! O conteúdo é bem estruturado e a didática é excelente. Para quem está começando com engenharia de dados no Google Cloud, este curso é um ótimo ponto de partida. Os laboratórios são essenciais para fixar o aprendizado."
"Curso excelente! Aborda de forma concisa e prática os principais serviços do GCP para engenharia de dados. Os labs são um diferencial. Recomendo fortemente."
"Os conceitos são explicados de forma simples e direta, o que facilita muito o aprendizado. Um curso introdutório excelente."
Oferece uma introdução clara e prática aos serviços de dados do GCP.
"Aprendi muito sobre como modernizar meus pipelines. Recomendo para quem busca uma base sólida no GCP."
"Perfeito para entender os fundamentos de BigQuery e Cloud Storage para data engineering. Os conceitos são explicados de forma simples e direta, o que facilita muito o aprendizado."
"Fiquei muito satisfeito com o curso. Ele me deu a base necessária para começar a trabalhar com dados no Google Cloud."
Pequenas inconsistências na qualidade do áudio em algumas seções.
"A qualidade do áudio poderia ser melhor em algumas partes."
Pode ser superficial para quem já tem experiência prévia na área.
"Apresenta os conceitos básicos, mas senti falta de aprofundamento. Para quem já tem alguma experiência, pode ser um pouco básico demais."
"No entanto, gostaria de ver mais exemplos práticos e talvez um projeto final mais robusto para aplicar o conhecimento."
"A única ressalva é que, como é introdutório, não se aprofunda em tópicos mais avançados, o que é compreensível."

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 em Português Brasileiro with these activities:
Review the basics of data lakes and data warehouses
This activity will help you lay a foundation for success in this course by reviewing the core concepts of data lakes and data warehouses.
Browse courses on Data Lake
Show steps
  • Read the provided materials on data lakes and data warehouses.
  • Create a simple data lake and data warehouse using your preferred tools.
  • Practice loading and querying data from your data lake and data warehouse.
Join a study group or online forum
Participating in a study group or online forum will allow you to connect with other learners, discuss course material, and get feedback on your understanding, which can greatly enhance your learning experience.
Browse courses on Collaboration
Show steps
  • Find a study group or online forum related to data engineering.
  • Actively participate in discussions and ask questions.
  • Share your knowledge and insights with others.
Review basic programming concepts
Reviewing basic programming concepts will strengthen your foundation and make it easier to learn the more advanced concepts covered in the course.
Browse courses on Programming
Show steps
  • Review your notes or textbooks on basic programming concepts.
  • Complete online tutorials or exercises on programming.
  • Try solving simple programming problems.
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Revise data modeling techniques
Reviewing data modeling techniques will help you better understand the different ways to structure and organize data, which is essential for building effective data pipelines.
Browse courses on Data Modeling
Show steps
  • Review your notes or textbooks on data modeling.
  • Complete online tutorials or exercises on data modeling.
  • Practice creating ER diagrams for sample datasets.
Practice querying data using SQL
Practicing querying data using SQL will strengthen your ability to extract valuable insights from data, which is a key skill for data engineers.
Browse courses on SQL
Show steps
  • Sign up for an online SQL practice platform.
  • Work through practice problems and exercises.
  • Try solving real-world data analysis problems using SQL.
Follow tutorials on building data pipelines with Google Cloud
This activity will help you develop the skills you need to build and manage data pipelines in Google Cloud.
Browse courses on Data Pipelines
Show steps
  • Find tutorials on building data pipelines with Google Cloud.
  • Follow the tutorials and complete all the exercises.
  • Deploy your data pipelines to your own Google Cloud project.
Compile a list of resources for data engineering
Compiling a list of resources for data engineering will provide you with a valuable reference that you can use throughout your learning journey.
Browse courses on Resources
Show steps
  • Search for online resources, articles, and tutorials on data engineering.
  • Organize the resources into categories, such as tools, techniques, and best practices.
  • Create a document or spreadsheet to store your list of resources.
Explore open-source tools for data pipelines
Exploring open-source tools for data pipelines will give you hands-on experience with the technologies used in the industry, broadening your knowledge and making you more competitive.
Browse courses on Apache Beam
Show steps
  • Research different open-source tools for data pipelines.
  • Follow tutorials or documentation to set up and use these tools.
  • Build a simple data pipeline using one of the tools.
Build a data pipeline for a real-world use case
This activity will give you hands-on experience in building and managing a data pipeline for a real-world use case.
Browse courses on Data Pipeline
Show steps
  • Identify a real-world use case for a data pipeline.
  • Design and build a data pipeline for your use case using Google Cloud.
  • Deploy your data pipeline to your own Google Cloud project.
  • Monitor and maintain your data pipeline.
Design a data pipeline for a real-world scenario
Designing a data pipeline for a real-world scenario will help you apply the concepts you've learned in the course to a practical problem, reinforcing your understanding and building your confidence.
Browse courses on Data Architecture
Show steps
  • Choose a real-world dataset and define a specific data analysis or business problem.
  • Design the data pipeline architecture, including data sources, transformations, and destination.
  • Create a document or presentation outlining your design.
Mentor a junior data engineer
Mentoring a junior data engineer will not only benefit them, but also reinforce your own understanding of data engineering concepts and help you develop your leadership skills.
Browse courses on Mentoring
Show steps
  • Find a junior data engineer who is looking for mentorship.
  • Set up regular meetings to provide guidance and support.
  • Share your knowledge and experience in data engineering.

Career center

Learners who complete Modernizing Data Lakes and Data Warehouses with GCP em Português Brasileiro will develop knowledge and skills that may be useful to these careers:
Database Architect
A Database Architect creates and maintains an organization's database management system. This course will provide foundational knowledge on the use of Google Cloud products such as Cloud Storage and BigQuery to create data lakes and data warehouses, which may be useful for career development.
Data Warehouse Engineer
A Data Warehouse Engineer designs and manages data warehouses. This course will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to create and manage data warehouses, which may be useful for career development.
Data Integration Engineer
A Data Integration Engineer designs and builds data integration solutions. This course will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to create and manage data integration solutions, which may be useful for career development.
Data Engineer
A Data Engineer builds and maintains data pipelines and infrastructure to store, process, and analyze data effectively. This course will provide foundational knowledge on the use of Google Cloud products such as Cloud Storage and BigQuery to create data lakes and data warehouses. In particular, the introduction to data engineering practices and principles may be useful for career development.
Data Architect
A Data Architect designs and manages data systems. This course will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to create and manage data storage solutions, which may be useful for career development.
Database Administrator
A Database Administrator manages and maintains an organization's database systems. This course will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to create and manage data storage solutions, which may be useful for career development.
Data Scientist
A Data Scientist develops and deploys machine learning and statistical models to analyze data and solve business problems. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and analyze data at scale.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to improve decision-making. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and analyze data to extract insights.
Business Intelligence Analyst
A Business Intelligence Analyst gathers, analyzes, and presents data to help organizations make informed decisions. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and analyze data to extract meaningful insights.
Cloud Architect
A Cloud Architect designs and manages cloud computing solutions. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to build and manage data storage and processing solutions in the cloud.
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and manage data for software applications.
Data Engineer Manager
A Data Engineer Manager leads and manages a team of data engineers. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to build and manage data engineering solutions.
Systems Analyst
A Systems Analyst studies how an organization's systems work together to meet business needs. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and analyze data to improve organizational efficiency.
Information Technology Administrator
An Information Technology Administrator manages and maintains an organization's IT systems and infrastructure. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and manage data for IT systems.
Information Architect
An Information Architect designs and manages an organization's information systems. This course may be useful for career development as it will provide foundational knowledge on the use of Google Cloud products, such as Cloud Storage and BigQuery, to store and manage data for information systems.

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 em Português Brasileiro.
Provides a comprehensive overview of data engineering with Google BigQuery. It great resource for anyone who wants to learn more about data engineering with BigQuery or who is looking for a reference book.
Classic in the field of data warehousing. It provides a comprehensive overview of the concepts, technologies, and applications of data warehousing. It great resource for anyone who wants to learn more about data warehousing or who is looking for a reference book.
Provides a comprehensive overview of data engineering on Google Cloud Platform. It great resource for anyone who wants to learn more about data engineering on GCP or who is looking for a reference book.
Provides a comprehensive overview of modern data warehousing with Google BigQuery. It great resource for anyone who wants to learn more about modern data warehousing with BigQuery or who is looking for a reference book.
Provides a comprehensive overview of data lakes and how they can be used to store and manage large volumes of data. It great resource for anyone who is new to data lakes or wants to learn more about them.
Provides a comprehensive overview of data mesh, a new architecture for data democratization. It great resource for anyone who wants to learn more about data mesh or who is looking for a reference book.

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