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Nestor Nicolas Campos Rojas
En este proyecto, vamos a aprender sobre el funcionamiento de AWS Data Pipeline ejecutando un proceso de ETL.
Register for this course and see more details by visiting:
OpenCourser.com/course/4cpldl/implementando
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What's inside
Syllabus
Visión general del proyecto
En este proyecto, vamos a aprender sobre el funcionamiento de AWS Data Pipeline ejecutando un proceso de ETL.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
El proyecto proporciona experiencia práctica con el proceso ETL en AWS Data Pipeline, lo que mejora las habilidades de los estudiantes en ingeniería de datos
El proyecto está diseñado para estudiantes con conocimientos previos de AWS Data Pipeline y técnicas ETL, lo que puede limitar la accesibilidad para principiantes
Save this course
Save Implementando AWS Data Pipeline to your list so you can find it easily later:
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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 Implementando AWS Data Pipeline with these
activities:
Revise Cloud Computing Concepts
Show steps
Refreshes your understanding of cloud computing concepts, which are essential for understanding AWS Data Pipeline.
Browse courses on
Cloud Computing
Show steps
-
Review notes from previous courses or online resources on cloud computing.
-
Practice deploying and managing virtual machines in a cloud environment.
Practice Data Transformation Techniques
Show steps
Strengthens your ability to transform data effectively, which is crucial for building efficient ETL pipelines in AWS Data Pipeline.
Browse courses on
Data Transformation
Show steps
-
Solve coding challenges or exercises that involve data transformation tasks.
-
Experiment with different data transformation tools and techniques.
-
Review and analyze real-world examples of data transformation pipelines.
Follow Tutorials on AWS Data Pipeline
Show steps
Provides practical guidance on using AWS Data Pipeline for ETL processes, which is the focus of this course.
Browse courses on
AWS Data Pipeline
Show steps
-
Identify relevant tutorials from AWS documentation or other trusted sources.
-
Follow the tutorials step-by-step, experimenting with different configurations and scenarios.
-
Troubleshoot any issues encountered while following the tutorials.
Three other activities
Expand to see all activities and additional details
Show all six activities
Discuss ETL Pipeline Designs and Implementations
Show steps
Encourages collaboration and knowledge sharing among peers, which can lead to innovative solutions and a deeper understanding of ETL pipeline concepts.
Browse courses on
AWS Data Pipeline
Show steps
-
Join or form a study group or online discussion forum.
-
Share ideas and experiences related to ETL pipeline design and implementation.
-
Provide feedback and collaborate on projects.
Build a Simple ETL Pipeline Using AWS Data Pipeline
Show steps
Provides hands-on experience in creating and managing an ETL pipeline using AWS Data Pipeline, which is a core skill for this course.
Show steps
-
Design the ETL pipeline, including data sources, transformations, and destination.
-
Create the pipeline using AWS Data Pipeline console or API.
-
Configure the pipeline to perform the desired data transformations.
-
Schedule the pipeline to run on a regular basis.
-
Monitor and troubleshoot the pipeline to ensure it runs smoothly.
Participate in AWS Data Pipeline Challenges
Show steps
Provides a motivating and practical way to apply your skills and knowledge of AWS Data Pipeline in a competitive environment.
Browse courses on
AWS Data Pipeline
Show steps
-
Identify and register for relevant AWS Data Pipeline challenges.
-
Design and implement a solution within the specified time frame.
-
Submit your solution and receive feedback from experts.
Revise Cloud Computing Concepts
Show steps
Refreshes your understanding of cloud computing concepts, which are essential for understanding AWS Data Pipeline.
Browse courses on
Cloud Computing
Show steps
Show steps
Show steps
- Review notes from previous courses or online resources on cloud computing.
- Practice deploying and managing virtual machines in a cloud environment.
Practice Data Transformation Techniques
Show steps
Strengthens your ability to transform data effectively, which is crucial for building efficient ETL pipelines in AWS Data Pipeline.
Browse courses on
Data Transformation
Show steps
Show steps
Show steps
- Solve coding challenges or exercises that involve data transformation tasks.
- Experiment with different data transformation tools and techniques.
- Review and analyze real-world examples of data transformation pipelines.
Follow Tutorials on AWS Data Pipeline
Show steps
Provides practical guidance on using AWS Data Pipeline for ETL processes, which is the focus of this course.
Browse courses on
AWS Data Pipeline
Show steps
Show steps
Show steps
- Identify relevant tutorials from AWS documentation or other trusted sources.
- Follow the tutorials step-by-step, experimenting with different configurations and scenarios.
- Troubleshoot any issues encountered while following the tutorials.
Three other activities
Expand to see all activities and additional details
Show all six activities
Discuss ETL Pipeline Designs and Implementations
Show steps
Encourages collaboration and knowledge sharing among peers, which can lead to innovative solutions and a deeper understanding of ETL pipeline concepts.
Browse courses on
AWS Data Pipeline
Show steps
Show steps
Show steps
- Join or form a study group or online discussion forum.
- Share ideas and experiences related to ETL pipeline design and implementation.
- Provide feedback and collaborate on projects.
Build a Simple ETL Pipeline Using AWS Data Pipeline
Show steps
Provides hands-on experience in creating and managing an ETL pipeline using AWS Data Pipeline, which is a core skill for this course.
Show steps
Show steps
Show steps
- Design the ETL pipeline, including data sources, transformations, and destination.
- Create the pipeline using AWS Data Pipeline console or API.
- Configure the pipeline to perform the desired data transformations.
- Schedule the pipeline to run on a regular basis.
- Monitor and troubleshoot the pipeline to ensure it runs smoothly.
Participate in AWS Data Pipeline Challenges
Show steps
Provides a motivating and practical way to apply your skills and knowledge of AWS Data Pipeline in a competitive environment.
Browse courses on
AWS Data Pipeline
Show steps
Show steps
Show steps
- Identify and register for relevant AWS Data Pipeline challenges.
- Design and implement a solution within the specified time frame.
- Submit your solution and receive feedback from experts.
Career center
Learners who complete Implementando AWS Data Pipeline will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers design and build pipelines to capture, transform, and store data. This process is known as ETL (Extract, Transform, Load), and AWS Data Pipeline is a popular tool for this purpose. This course will help you develop the skills you need to succeed as a Data Engineer by introducing you to the concepts and techniques of AWS Data Pipeline.
ETL Developer
ETL Developer
ETL Developers design and build ETL (Extract, Transform, Load) processes. AWS Data Pipeline is a popular tool for ETL Developers because it can be used to automate the data ingestion and processing tasks that are essential for ETL processes. This course will help you build a foundation in AWS Data Pipeline so that you can use it to design and build more efficient and scalable ETL processes.
Big Data Engineer
Big Data Engineer
Big Data Engineers design and manage systems for storing and processing large amounts of data. AWS Data Pipeline is a powerful tool for Big Data Engineers because it can be used to automate the data ingestion and processing tasks that are essential for Big Data applications. This course will help you develop the skills you need to succeed as a Big Data Engineer by introducing you to the concepts and techniques of AWS Data Pipeline.
Data Scientist
Data Scientist
Data Scientists use data to build models that can predict future outcomes. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Data Scientists. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your data science workflow.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and insights. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Data Analysts. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your data analysis workflow.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and build machine learning models. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Machine Learning Engineers. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your machine learning workflow.
Data Warehouse Engineer
Data Warehouse Engineer
Data Warehouse Engineers design and manage data warehouses. AWS Data Pipeline is a popular tool for Data Warehouse Engineers because it can be used to automate the data ingestion and processing tasks that are essential for data warehouses. This course will help you build a foundation in AWS Data Pipeline so that you can use it to design and manage more efficient and scalable data warehouses.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing solutions. AWS Data Pipeline is a popular tool for Cloud Architects because it can be used to automate the data ingestion and processing tasks that are essential for cloud applications. This course will help you build a foundation in AWS Data Pipeline so that you can use it to design and manage more efficient and scalable cloud solutions.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. AWS Data Pipeline is a popular tool for Software Engineers because it can be used to automate the data ingestion and processing tasks that are essential for software applications. This course will help you build a foundation in AWS Data Pipeline so that you can use it to develop more efficient and scalable software applications.
Business Analyst
Business Analyst
Business Analysts use data to make better decisions. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Business Analysts. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your business analysis workflow.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. AWS Data Pipeline can be used to automate the data ingestion and processing tasks that are essential for databases. This course will help you build a foundation in AWS Data Pipeline so that you can use it to manage and maintain databases more efficiently.
Sales Analyst
Sales Analyst
Sales Analysts use data to track sales performance. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Sales Analysts. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your sales analysis workflow.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to measure the effectiveness of marketing campaigns. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Marketing Analysts. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your marketing analysis workflow.
Product Manager
Product Manager
Product Managers design and manage products. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Product Managers. This course will help you build a foundation in AWS Data Pipeline so that you can use it to design and manage more successful products.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. AWS Data Pipeline can be used to automate the data collection and processing tasks that are essential for Financial Analysts. This course will help you build a foundation in AWS Data Pipeline so that you can use it to streamline your financial analysis workflow.
For more career information including salaries, visit:
OpenCourser.com/course/4cpldl/implementando
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
Implementando AWS Data Pipeline.
Save
Este libro proporciona una base sólida en el diseño de aplicaciones intensivas en datos. Aunque no cubre AWS Data Pipeline específicamente, proporciona información valiosa sobre patrones y técnicas de diseño que son aplicables a cualquier solución de canalización de datos.
Este libro proporciona una guía completa para diseñar, implementar y administrar canalizaciones de datos en AWS. Cubre una amplia gama de temas, incluyendo la arquitectura de canalizaciones de datos, el procesamiento de datos y la gestión de metadatos.
Este libro ofrece una amplia descripción de la arquitectura de Big Data, cubriendo temas como el almacenamiento de datos, el procesamiento de datos y el análisis. Proporciona una valiosa perspectiva sobre los desafíos y las mejores prácticas de diseñar e implementar canalizaciones de datos a gran escala.
Provides a comprehensive overview of dimensional modeling, a popular data modeling technique for data warehouses. It covers all aspects of the technique, from design to implementation.
Save
Este libro proporciona una visión general de la gestión de datos para análisis. Aunque no cubre AWS Data Pipeline específicamente, proporciona información valiosa sobre las estrategias y herramientas de gestión de datos que son esenciales para construir canalizaciones de datos efectivas.
Provides a comprehensive overview of big data analytics and its applications. It covers a wide range of topics, including data sources, data processing, and data analysis.
Provides a comprehensive overview of Hadoop, a popular open-source framework for big data processing. It covers all aspects of the software, from installation and configuration to programming and administration.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4cpldl/implementando
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Effort
1 hora de trabajo
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Nestor Nicolas Campos Rojas
Language
Español
Good to know
El proyecto proporciona experiencia práctica con el proceso ETL en AWS Data Pipeline, lo que mejora las habilidades de los estudiantes en ingeniería de datos
El proyecto está diseñado para estudiantes con conocimientos previos de AWS Data Pipeline y técnicas ETL, lo que puede limitar la accesibilidad para principiantes
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