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 each architecture to help data professionals understand its pros and cons.
In the process, 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. By reading this book, you'll:
Gain a working understanding of several data architectures
Know the pros and cons of each approach
Distinguish data architecture theory from the reality
Learn to 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
Alleviate confusion by clearly defining each data architecture
Know what architectures to use for each cloud provider
Comments need intelligible text (not only emojis or meaningless drivel). No upload requests, visit the forum or message the uploader for this. Use common sense and try to stay on topic.