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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"etl"에 대한 112개의 결과

IBM Skills Network
BI Foundations with SQL, ETL and Data Warehousing
획득할 기술: Apache, Business Analysis, Cloud Computing, Cloud Engineering, Computer Architecture, Computer Programming, Data Management, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Databases, Extract, Transform, Load, Interactive Data Visualization, Microarchitecture, Programming Principles, Python Programming, SQL, Software Architecture, Software Engineering, Statistical Programming, Theoretical Computer Science
4.6
(16.2k개의 검토)
Beginner · Specialization · 3-6 Months
IBM Skills Network
IBM Data Engineering
획득할 기술: Algorithms, Apache, Big Data, Business Analysis, Cloud Computing, Cloud Engineering, Computational Logic, Computational Thinking, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Data Architecture, Data Engineering, Data Management, Data Model, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Database Design, Database Theory, Databases, DevOps, Distributed Computing Architecture, Extract, Transform, Load, Graph Theory, Hardware Design, IBM Cloud, Interactive Data Visualization, Kubernetes, Leadership and Management, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Network Architecture, Network Security, NoSQL, PostgreSQL, Professional Development, 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
(36k개의 검토)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Warehouse Engineer
획득할 기술: Apache, Big Data, Business Analysis, Cloud Computing, Cloud Engineering, Computer Architecture, Computer Networking, Computer Programming, Data Architecture, Data Engineering, Data Management, Data Model, Data Visualization, Data Visualization Software, Data Warehousing, Database Administration, Database Application, Database Design, Databases, DevOps, Distributed Computing Architecture, Extract, Transform, Load, Hardware Design, Interactive Data Visualization, Leadership and Management, Microarchitecture, Network Security, NoSQL, PostgreSQL, Professional Development, 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
(17.1k개의 검토)
Beginner · Professional Certificate · 3-6 Months
IBM Skills Network
IBM Data Science
획득할 기술: Algebra, Algorithms, Analysis, Business Analysis, Communication, Computational Logic, Computer Programming, Computer Programming Tools, Correlation And Dependence, Data Analysis, Data Management, Data Mining, Data Structures, Data Visualization, Database Administration, Database Application, Databases, Econometrics, Entrepreneurship, Exploratory Data Analysis, Extract, Transform, Load, General Statistics, Geovisualization, Interactive Data Visualization, Machine Learning, Machine Learning Algorithms, Marketing, Mathematical Theory & Analysis, Mathematics, Plot (Graphics), Probability & Statistics, Python Programming, R Programming, Regression, SPSS, SQL, Spreadsheet Software, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Supply Chain Systems, Supply Chain and Logistics, Theoretical Computer Science
4.6
(96.5k개의 검토)
Beginner · Professional Certificate · 3-6 Months
University of Colorado System
Data Warehousing for Business Intelligence
획득할 기술: Accounting, Business Analysis, Business Intelligence, Computational Logic, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Data Architecture, Data Management, Data Mining, Data Visualization, Data Warehousing, Database Administration, Database Application, Database Design, Database Theory, Databases, Decision Making, Entrepreneurship, Extract, Transform, Load, Leadership and Management, Linear Algebra, Mathematical Theory & Analysis, Mathematics, Modeling, PostgreSQL, Programming Principles, SQL, Spreadsheet Software, Statistical Programming, Theoretical Computer Science
4.5
(3.6k개의 검토)
Advanced · Specialization · 3-6 Months
University of California, Irvine
Database Design and Operational Business Intelligence
획득할 기술: Accounting, Basic Descriptive Statistics, Big Data, Business Analysis, Business Intelligence, Communication, Data Analysis, Data Management, Data Mining, Data Model, Data Visualization, Data Warehousing, Database Administration, Database Application, Database Design, Databases, Extract, Transform, Load, General Statistics, Machine Learning, Machine Learning Algorithms, Marketing, NoSQL, Probability & Statistics, Regression, SAS (Software), SQL, Statistical Analysis, Statistical Programming
4.4
(89개의 검토)
Beginner · Specialization · 1-3 Months
Google
Google Data Analytics
획득할 기술: Algorithms, Analysis, Application Development, Bias, Big Data, Budget Management, Business Analysis, Business Communication, Change Management, Cloud Computing, Communication, Computational Logic, Computer Architecture, Computer Networking, Computer Programming, Computer Programming Tools, Cryptography, Data Analysis, Data Analysis Software, Data Management, Data Mining, Data Model, Data Structures, Data Type, Data Visualization, Data Visualization Software, Database Administration, Database Design, Databases, Decision Making, Design and Product, Distributed Computing Architecture, Entrepreneurship, Extract, Transform, Load, Feature Engineering, Finance, Financial Analysis, Full-Stack Web Development, General Statistics, Interactive Data Visualization, Leadership and Management, Machine Learning, Mathematical Theory & Analysis, Mathematics, Metadata, Network Security, Other Programming Languages, Plot (Graphics), Presentation, Privacy, Probability & Statistics, Problem Solving, Product Design, Programming Principles, Project Management, R Programming, Research and Design, SQL, Security Engineering, Security Strategy, Small Data, Software Engineering, Software Security, Spreadsheet Software, Statistical Analysis, Statistical Programming, Storytelling, Strategy and Operations, Tableau Software, Theoretical Computer Science, Visual Design, Web Development
4.8
(71.7k개의 검토)
Beginner · Professional Certificate · 3-6 Months
MathWorks
Practical Data Science with MATLAB
획득할 기술: Algebra, Analysis, Applied Machine Learning, Business Analysis, Correlation And Dependence, Data Analysis, Data Analysis Software, Data Management, Data Visualization, Econometrics, Exploratory Data Analysis, Extract, Transform, Load, Feature Engineering, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematics, Matlab, Plot (Graphics), Predictive Modelling, Probability & Statistics, Probability Distribution, Regression, Statistical Analysis, Statistical Visualization, Web Development
4.7
(929개의 검토)
Beginner · Specialization · 3-6 Months

etl processing on google cloud using dataflow and bigquery

bi foundations with sql, etl and data warehousing

요약하자면, 여기에 가장 인기 있는 etl 강좌 10개가 있습니다.

BI Foundations with SQL, ETL and Data Warehousing: IBM Skills Network
IBM Data Engineering: IBM Skills Network
IBM Data Warehouse Engineer: IBM Skills Network
Extract, Transform, and Load Data: CertNexus
ETL and Data Pipelines with Shell, Airflow and Kafka: IBM Skills Network
IBM Data Science: IBM Skills Network
Data Warehousing for Business Intelligence: University of Colorado System
Database Design and Operational Business Intelligence: University of California, Irvine
Google Data Analytics: Google
Practical Data Science with MATLAB: MathWorks

Machine Learning에서 학습할 수 있는 스킬

Etl에 대한 자주 묻는 질문

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.‎