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Understanding the concepts of Data Engineering starts with understanding the fundamentals. On your way to mastery, it's crucial for you to understand how certain concepts were derived, and why things work like they do. Starting with these resources is the best way to do so.
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The first edition of Ralph Kimball's The Data Warehouse Toolkit introduced the industry to dimensional modeling,and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehe…
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dbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps.
This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build …
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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, strea…
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Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct…
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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, strea…
Recommended by the experts and mentors at MentorCruise.
These books are not required for you to learn Data Engineering, but they are highly recommended for you to deepen your knowledge.
Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by …
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Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientis…
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Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in t…
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You've got your basics in order – time to move on to some advanced and specialized concepts. Data Engineering is evolving every day, these books can help you master it.
The Database and Expert Systems Application -DEXA - conferences are mainly oriented to establish a state-of-the art forum on Database and Expert System applications. But Practice without Theory has no sense, as Leonardo said five centuries ago. In this Conference we try a comprornise between the…
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Advanced Topics in Database Research is a series of books on the fields of database, software engineering, and systems analysis and design. They feature the latest research ideas and topics on how to enhance current database systems, improve information storage, refine existing database models, …
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