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ETL con Python
Creando pipeline básico
Andrés Escuadra
Andrés Escuadra
En este proyecto guiado de 1 hora de duración, aprenderás a resolver problemas reales como el "excel caos".
Read more
En este proyecto guiado de 1 hora de duración, aprenderás a resolver problemas reales como el "excel caos".
Read more
En este proyecto guiado de 1 hora de duración, aprenderás a resolver problemas reales como el "excel caos".
Este proyecto es para quienes buscan insertarse en ciencia de datos y aprender a utilizar herramientas para cargar datos desde un csv, realizar transformación de los mismos y cargarlos en una base tipo SQL.
Dado que utilizaremos Google Colab, se necesitará capacidad para interactuar con notebook de esa plataforma, una cuenta de gmail y conocimientos previos sobre variables y condicionales en Python.
Si deseas aprovechar al máximo todo el poder de los datos, este proyecto guiado es para ti.
Register for this course and see more details by visiting:
OpenCourser.com/course/p8cxhe/etl
What's inside
Syllabus
Visión general del proyecto
Este Proyecto Guiado ETL con Python : Creando pipeline básico, es de nivel Intermedio.
En este curso basado en proyectos de 1 hora de duración, aprenderás a resolver problemas reales como el "excel caos" .
Este proyecto es para quienes buscan insertarse en ciencia de datos y aprender a utilizar herramientas para cargar datos desde un csv, realizar transformación de los mismos y cargarlos en una base tipo SQL.
Dado que utilizaremos Google Colab se necesitará capacidad para interactuar con notebook de esa plataforma, una cuenta de gmail y conocimientos previos sobre variables y condicionales en Python.
Si deseas aprovechar al máximo todo el poder de los datos, este proyecto guiado es para tí.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Diseñado para personas que buscan comenzar en el campo de la ciencia de datos
Enseña a utilizar herramientas para cargar datos desde archivos CSV y transformarlos para cargarlos en una base de datos SQL
Requiere conocimientos previos en programación Python, incluyendo variables y condicionales
Utiliza Google Colab, lo que requiere familiaridad con su plataforma y una cuenta de Google
Tiene una duración limitada de 1 hora, lo que puede ser breve para cubrir todos los conceptos en detalle
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Activities
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ETL con Python: Creando pipeline básico.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete ETL con Python: Creando pipeline básico will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts examine large data sets to uncover patterns and trends, devising solutions to complex business problems. They help organizations make informed decisions based on data-driven insights. This course provides a solid foundation in data wrangling and transformation, two essential skills for Data Analysts. By learning to load, clean, and prepare data, you'll be well-equipped to contribute to the data-driven decision-making process.
Business Analyst
Business Analyst
Business Analysts bridge the gap between business and technology, translating business requirements into technical solutions. They play a vital role in ensuring that data-driven insights are used effectively to improve business outcomes. This course provides a foundation in data wrangling and transformation, helping Business Analysts understand the data landscape and contribute to data-driven decision-making.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure and processes that support data-driven organizations. They ensure the reliability, scalability, and security of data systems. This course offers hands-on experience with data loading and transformation, providing a valuable foundation for Data Engineers.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and deploy machine learning models to solve complex business problems. They combine expertise in data engineering, machine learning, and software engineering. This course offers a strong foundation in data transformation, a critical skill for Machine Learning Engineers.
Data Architect
Data Architect
Data Architects design and implement data management strategies, ensuring that data is organized, accessible, and usable. They play a key role in data governance and ensuring data quality. This course provides a foundation in data loading and transformation, essential skills for Data Architects.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts create visual representations of data to communicate insights and trends. They help users understand data quickly and easily. This course provides a foundation in data wrangling and transformation, essential skills for creating effective data visualizations.
Database Administrator
Database Administrator
Database Administrators manage and maintain database systems, ensuring their performance, reliability, and security. They oversee data loading, storage, and retrieval. This course offers practical experience with data loading and transformation, providing a valuable foundation for Database Administrators.
Data Quality Analyst
Data Quality Analyst
Data Quality Analysts ensure the accuracy, completeness, and consistency of data. They play a vital role in data governance and ensuring data integrity. This course provides a foundation in data wrangling and transformation, providing valuable skills for Data Quality Analysts.
Data Scientist
Data Scientist
Data Scientists leverage data to build models, solve complex problems, and predict future outcomes. They use their expertise in statistics, machine learning, and data analysis to drive innovation and decision-making. This course provides a practical introduction to data wrangling and transformation, which are critical skills for Data Scientists.
Data Governance Analyst
Data Governance Analyst
Data Governance Analysts develop and implement policies and procedures to ensure the proper use of data within organizations. They ensure compliance with regulations and ethical guidelines. This course provides a foundation in data wrangling and transformation, essential skills for Data Governance Analysts.
Information Architect
Information Architect
Information Architects design and organize the structure and content of websites, intranets, and other information systems. They ensure that information is easy to find, understand, and use. This course provides a foundation in data wrangling and transformation, helping Information Architects understand the data landscape and organize information effectively.
Research Analyst
Research Analyst
Research Analysts gather, analyze, and interpret data to provide insights and recommendations. They work in various industries, including finance, healthcare, and market research. This course provides a foundation in data wrangling and transformation, essential skills for Research Analysts.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to extract meaningful insights. They use statistical methods to solve problems, draw conclusions, and make predictions. This course provides hands-on experience with data wrangling and transformation, enhancing the skills needed for effective statistical analysis.
Knowledge Manager
Knowledge Manager
Knowledge Managers develop and implement strategies for capturing, organizing, and sharing knowledge within organizations. They ensure that knowledge is accessible and usable by employees. This course provides a foundation in data wrangling and transformation, helping Knowledge Managers understand the data landscape and manage knowledge effectively.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They write code, debug systems, and ensure software quality. This course provides a foundation in data loading and transformation, which are essential skills for Software Engineers working with data-intensive applications.
For more career information including salaries, visit:
OpenCourser.com/course/p8cxhe/etl
Reading list
We've selected five 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
ETL con Python: Creando pipeline básico.
Este libro es un recurso práctico que enseña cómo utilizar Python para el análisis de datos, incluyendo la manipulación de datos, la visualización de datos y el modelado de datos. Es esencial para aquellos que quieran utilizar Python para tareas ETL.
Este libro clásico presenta el enfoque de Inmon para el diseño y la implementación de almacenes de datos. Es una lectura fundamental para aquellos que buscan una comprensión profunda de los principios y prácticas subyacentes de ETL.
Este libro proporciona una visión integral de los almacenes de datos, incluyendo el diseño, la implementación y el mantenimiento. Es una lectura valiosa para aquellos que buscan comprender el contexto más amplio de las tecnologías ETL.
Este libro cubre conceptos esenciales de Python para el análisis de datos, incluidos los conceptos básicos de manipulación de datos y transformación necesarios para el proceso ETL.
Save
Este libro ofrece una visión general de la ingeniería de datos, incluyendo el papel de ETL en el ciclo de vida de los datos. Es una lectura útil para aquellos que buscan comprender el contexto más amplio y las prácticas de la ingeniería de datos.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/p8cxhe/etl
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Effort
1 hora 20 minutos
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Andrés Escuadra
Language
Español
Good to know
Diseñado para personas que buscan comenzar en el campo de la ciencia de datos
Enseña a utilizar herramientas para cargar datos desde archivos CSV y transformarlos para cargarlos en una base de datos SQL
Requiere conocimientos previos en programación Python, incluyendo variables y condicionales
Utiliza Google Colab, lo que requiere familiaridad con su plataforma y una cuenta de Google
Tiene una duración limitada de 1 hora, lo que puede ser breve para cubrir todos los conceptos en detalle
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