This book details data engineering from data collection to insights. A practical reference for data engineers, IT professionals, and analysts to master modern data engineering basics and advanced approaches.
This book provides a strong start by introducing data engineering's evolution, fundamental principles, and critical technologies. Next, data acquisition and storage are examined, covering data extraction, relational vs. NoSQL databases, and cloud storage. Then it discusses data processing and transformation, including ETL procedures, real-time processing, and data integration techniques.
Data quality and good visualisation are essential for useful reports, which the book covers in important metrics, validation methodologies, and visualisation technologies. Security, privacy, encryption, access management, and global data regulations are covered.
Ending with 'Advance topics' including machine learning integration, big data technologies, and cloud data engineering, the part looks ahead to industry developments. Data engineering students must read this book for theory, applications, and multiple-choice tests.
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