| Title | : | Fundamentals of Data Engineering: Plan and Build Robust Data Systems |
| Author | : | |
| Rating | : | |
| ISBN | : | 1098108302 |
| ISBN-10 | : | 1098108302 |
| Language | : | English |
| Format Type | : | and 1 more , Kindle Edition, Paperback |
| Number of Pages | : | 446 pages |
| Publication | : | OReilly Media; 1st edition (July 26 2022) |
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle.
Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology.
This book will help you:
Get a concise overview of the entire data engineering landscapeAssess data engineering problems using an end to end framework of best practicesCut through marketing hype when choosing data technologies, architecture, and processesUse the data engineering lifecycle to design and build a robust architectureIncorporate data governance and security across the data engineering lifecycleFundamentals of Data Engineering: Plan and Build Robust Data Systems Reviews
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With a background as database developer, I faced a lot of projects that were focused on ETL tasks using a traditional relational database like Oracle. Then, Hadoop and Kafka reached the scene during the Big Data eruption. The different data tools available started to be overwhelming.This book dissects the main steps that you need to focus to accomplish your goal, what technology is the most appropriate to support them and considerations about patterns that you need to take into account.One topic that I felt that was briefly discussed is schema management and evolution.
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Es existiert leider viel zu wenig Standard Literatur zu dem Thema Data Engineering, Reis & Housley ändern das nun. Es bietet nicht nur Berufseinsteigern einen guten Überblick über den Themenkomplex Data Engineering, es bringt eben auch einen Konsens mit. Gewohnt von der guten Qualität von O'Reilly definitiv ein guter Kauf! Gerade mit Data Management at Scale finde ich das vermittelte Wissen echt spitze!Je nach Bedarf muss man natürlich dann in die Tiefe gehen :)
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Finished reading the Fundamentals of Data Engineering. It was a pleasurable and useful reading. It really delivers on the title. It gives a good foundation of the current state of DE. Puts into perspective old ideas that are still valid at the same time recognises old ideas that are obsolete in a current world. It lays a good foundational framework of what will stay in DE probably for a long time which is what they call the Data Engineering Life Cycle. I learned a lot about new hot topics, patterns and best practices. I would highly recommend to any experienced or aspirational DE to read. Congrats on the great work
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This book has mostly references to other frameworks/contents but lacks its own content of any value, that can be applied to a project
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Recomendo muito a leitura desse livro para aqueles que gostam de engenharia de dados, pessoas que querem entender o que faz um engenheiro de dados, entender os conceitos relacionados a área de uma forma que foca nos conceitos que tendem a durar ao longo dos anos (ao contrário das ferramentas). É uma leitura necessária para quem quer seguir nessa área seja como engenheiro de dados ou afins.
