ETL is an acronym for extract, transform, load. This describes a computer programming process that automatically extracts, transforms, and loads multiple forms of computer data from a variety of data sources, and then transmits them to a data storage facility or data warehouse repository. ETL was introduced half a century ago in computing circles to help computer techs better integrate and load data into large computer mainframes for computation purposes and data analysis. The ETL process was originally designed to support business intelligence needs. It is still used today, generally for smaller repositories of data, and other forms of data integration software are being used for larger volumes of data.

Why is it important to learn about ETL?

Learning about ETL can help you further your data storage knowledge, which is such a huge part of today's interconnected networks. Knowing ETL will help you understand why companies use the process to sort through their data, decide what to keep, and what to eliminate. Learning ETL can help you manage data projects more efficiently. This is especially true for anyone eager to learn about scalable data analytics processes and optimal business intelligence warehousing.

What type of careers use ETL?

The typical careers for someone who has learned ETL include data warehousing, data storage, network functionality, computer networking, systems architecture, and other similar roles within companies or agencies. Realistically, you could work in just about any data-intensive industry and find employment as an ETL developer. Many industries are moving toward big data repositories, and having the knowledge of ETL processes can be a tremendous asset for someone aspiring to find ETL work.

How can taking online courses help me learn ETL?

When you take online courses about ETL, you can learn the basics of data warehousing for business intelligence. But that's just the start. Within the wide variety of online courses about ETL, you can branch-off to pursue your interests in data warehousing, data storage, SQL database learning, visual modeling, and much more. Learning about these interconnected specialties can help you stay ahead of the big data revolution.

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IBM
IBM Data Engineering
Habilidades que obtendrás: Apache, Big Data, Cloud Computing, Cloud Engineering, Computational Logic, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Data Architecture, Data Management, Data Warehousing, Database Administration, Database Application, Database Design, Database Theory, Databases, DevOps, Distributed Computing Architecture, Extract, Transform, Load, Hardware Design, IBM Cloud, Kubernetes, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Mysql, Network Architecture, Network Security, NoSQL, PostgreSQL, Probability & Statistics, Programming Principles, Project Management, Python Programming, Regression, SQL, Security Engineering, Security Strategy, Software Architecture, Software Engineering, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.6
(34.7k reseñas)
Beginner · Professional Certificate
IBM
BI Foundations with SQL, ETL and Data Warehousing
Habilidades que obtendrás: Apache, Cloud Computing, Cloud Engineering, Computer Architecture, Computer Programming, Computer Programming Tools, Data Management, Data Warehousing, Database Administration, Database Application, Databases, Extract, Transform, Load, Microarchitecture, Programming Principles, Python Programming, SQL, Software Architecture, Software Engineering, Statistical Programming, Theoretical Computer Science
4.6
(15.7k reseñas)
Beginner · Specialization
IBM
IBM Data Warehouse Engineer
Habilidades que obtendrás: Apache, Big Data, Cloud Computing, Cloud Engineering, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Data Architecture, Data Management, Data Warehousing, Database Administration, Database Application, Database Design, Databases, DevOps, Distributed Computing Architecture, Extract, Transform, Load, Hardware Design, Microarchitecture, Mysql, Network Security, PostgreSQL, Programming Principles, Project Management, Python Programming, SQL, Security Engineering, Security Strategy, Software Architecture, Software Engineering, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.6
(16.5k reseñas)
Beginner · Professional Certificate
Google
Google Data Analytics
Habilidades que obtendrás: Algorithms, Analysis, Application Development, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Econometrics, Entrepreneurship, Experiment, Extract, Transform, Load, Feature Engineering, Finance, General Statistics, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Network Security, Other Programming Languages, Plot (Graphics), Presentation, Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Statistical Visualization, Storytelling, Strategy and Operations, Theoretical Computer Science
4.8
(63k reseñas)
Beginner · Professional Certificate
University of Colorado System
Data Warehousing for Business Intelligence
Habilidades que obtendrás: Accounting, Algebra, Apache, Big Data, Business Analysis, Business Intelligence, Computational Logic, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Data Analysis Software, Data Architecture, Data Management, Data Mining, Data Model, Data Visualization, Data Warehousing, Database Administration, Database Application, Database Design, Database Theory, Databases, Extract, Transform, Load, Linear Algebra, Mathematical Theory & Analysis, Mathematics, PostgreSQL, Probability & Statistics, Programming Principles, SQL, Spreadsheet Software, Statistical Programming, Theoretical Computer Science
4.5
(3.6k reseñas)
Advanced · Specialization
IBM
Data Engineering Foundations
Habilidades que obtendrás: Apache, Big Data, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Data Architecture, Data Management, Data Warehousing, Database Administration, Database Application, Database Design, Databases, Distributed Computing Architecture, Extract, Extract, Transform, Load, Mathematical Theory & Analysis, Mathematics, Network Security, PostgreSQL, Project Management, Python Programming, SQL, Security Engineering, Security Strategy, Statistical Programming, Strategy and Operations, Theoretical Computer Science
4.6
(34.3k reseñas)
Beginner · Specialization

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En síntesis, estos son los 10 cursos más populares etl

IBM Data Engineering: IBM
BI Foundations with SQL, ETL and Data Warehousing: IBM
IBM Data Warehouse Engineer: IBM
Extract, Transform, and Load Data: CertNexus
ETL and Data Pipelines with Shell, Airflow and Kafka: IBM
Database Design and Operational Business Intelligence: University of California, Irvine
Prepare, Clean, Transform, and Load Data using Power BI: Coursera Project Network
Google Data Analytics: Google
Data Warehousing for Business Intelligence: University of Colorado System
Data Engineering Foundations: IBM

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Preguntas frecuentes sobre Etl

ETL is an acronym for extract, transform, load. This describes a computer programming process that automatically extracts, transforms, and loads multiple forms of computer data from a variety of data sources, and then transmits them to a data storage facility or data warehouse repository.
ETL was introduced half a century ago in computing circles to help computer techs better integrate and load data into large computer mainframes for computation purposes and data analysis. The ETL process was originally designed to support business intelligence needs. It is still used today, generally for smaller repositories of data, and other forms of data integration software are being used for larger volumes of data.‎
Learning about ETL can help you further your data storage knowledge, which is such a huge part of today's interconnected networks. Knowing ETL will help you understand why companies use the process to sort through their data, decide what to keep, and what to eliminate.
Learning ETL can help you manage data projects more efficiently. This is especially true for anyone eager to learn about scalable data analytics processes and optimal business intelligence warehousing.‎
The typical careers for someone who has learned ETL include data warehousing, data storage, network functionality, computer networking, systems architecture, and other similar roles within companies or agencies. Realistically, you could work in just about any data-intensive industry and find employment as an ETL developer. Many industries are moving toward big data repositories, and having the knowledge of ETL processes can be a tremendous asset for someone aspiring to find ETL work.‎
When you take online courses about ETL, you can learn the basics of data warehousing for business intelligence. But that's just the start. Within the wide variety of online courses about ETL, you can branch-off to pursue your interests in data warehousing, data storage, SQL database learning, visual modeling, and much more. Learning about these interconnected specialties can help you stay ahead of the big data revolution.‎

Se puso a disposición este contenido de preguntas frecuentes solo con fines informativos. Se les pide a los estudiantes que realicen investigaciones adicionales para asegurarse de que los cursos y otras credenciales cumplan con sus objetivos personales, profesionales y financieros.