Top 7 Best data engineering books (2022)

1. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

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2. Data Engineering with Apache Spark, Delta Lake, and Lakehouse: Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way

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3. Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing

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4. The Art of Doing Science and Engineering: Learning to Learn

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5. Rocketbook Smart Reusable Notebook – Dot-Grid Eco-Friendly Notebook with 1 Pilot Frixion Pen & 1 Microfiber Cloth Included – Infinity Black Cover, Executive Size (6″ x 8.8″), Model Number: EVR-E-K-A

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• No more wasting paper – this 36 page dotted grid notebook can be used endlessly by wiping clean with a damp cloth
• Blast your handwritten notes to popular cloud services like Google drive Dropbox Evernote box OneNote Slack iCloud email and more using the free Rocketbook application for iOS and Android
• Allow 15 seconds for ink from any Pilot Frixion pen marker or highlighter to dry in order for it to bond to our specialized pages
• Sophisticated AI technology allows you to use Rocketbook’s smart titles smart search and email transcription for easier naming and searching of your notes
• Includes 1 Rocketbook Core (formerly known as Everlast) Executive Size (6″ x 8 8″) Notebook 1 Pilot Frixion Pen and 1 Microfiber Cloth Note package may reflect “Everlast”

6. Machine Learning Engineering

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7. 97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts

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8. Data Engineering with Python: Work with massive datasets to design data models and automate data pipelines using Python

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9. Data Pipelines Pocket Reference: Moving and Processing Data for Analytics

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10. Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

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