I’m thrilled to share that after 15 months of dedicated effort, my book, “Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh,” is now available in eBook/Kindle format on Amazon! The journey to this moment has been incredibly rewarding, and I’m excited for you to see the result. The paperback edition will be available in about 2-3 weeks. You can order the eBook on Amazon here (for USA). And I would greatly appreciate any Amazon reviews! The book is being rolled out to other online stores, and some may have it at a lower price than Amazon (UPDATE: Barnes & Noble has the lowest eBook price so far).
Below is the abstract. The TOC and editorial reviews can be found here. Please send me any feedback on the book to jamesserra3@gmail.com. Would love to hear what you think!
Abstract
Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they’re also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.
James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You’ll learn what data lakehouses can help you achieve, and how to distinguish data mesh hype from reality. Best of all, you’ll be able to determine the most appropriate data architecture for your needs. With this book, you’ll:
- Gain a working understanding of several data architectures
- Learn the strengths and weaknesses of each approach
- Distinguish data architecture theory from the reality
- Pick the best architecture for your use case
- Understand the differences between data warehouses and data lakes
- Learn common data architecture concepts to help you build better solutions
- Explore the historical evolution and characteristics of data architectures.
- Learn essentials of running an architecture design session, team organization, and project success factors
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