This course provides a comprehensive guide to mastering data engineering, where you'll learn to build robust data pipelines, delve into ETL (Extract, Transform, Load) processes, and handle large datasets using Hadoop. You will gain expertise in extracting data from various sources, transforming it into a usable format, and loading it into data warehouses or big data platforms. With hands-on experience in Hadoop, the industry-standard framework for handling massive datasets, you’ll learn to manage and process massive datasets efficiently. Whether you're a beginner or an experienced professional, this course equips you with the skills to design, implement, and manage data pipelines, making you a valuable asset in any data-focused organization.
Expérience recommandée
Ce que vous apprendrez
Analyse the architecture and components of data pipelines to understand their impact on data flow and processing efficiency.
Implement robust ETL processes, for scalability and maintainability.
Analyze big data challenges and introduce Hadoop ecosystem tools (HDFS, MapReduce, Hive, Pig, and Spark) for data processing tasks.
Compétences que vous acquerrez
- Catégorie : Hadoop Ecosystem
- Catégorie : Data Storage Solutions
- Catégorie : Data Analysis
- Catégorie : Scalability
- Catégorie : Data Pipelines
Détails à connaître
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septembre 2024
1 devoir
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Il y a un module dans ce cours
This course provides a comprehensive guide to mastering data engineering, where you'll learn to build robust data pipelines, delve into ETL (Extract, Transform, Load) processes, and handle large datasets using Hadoop. You will gain expertise in extracting data from various sources, transforming it into a usable format, and loading it into data warehouses or big data platforms.
Inclus
12 vidéos4 lectures1 devoir2 sujets de discussion
Instructeur
Offert par
Recommandé si vous êtes intéressé(e) par Data Analysis
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Coursera Instructor Network
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