Название: Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data MeshАвтор: James Serra
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 278
Язык: английский
Формат: pdf (true), epub (true)
Размер: 12.7 MB
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
I have written this book for anyone with an interest in getting value out of data, whether you’re a database developer or administrator, a data architect, a CTO or CIO, or even someone in a role outside of IT. You could be early in your career or a seasoned veteran. The only skills you need are a little familiarity with data from your work and a sense of curiosity.
For readers with less experience with these topics, I provide an overview of big data (Chapter 1) and data architectures (Chapter 2), as well as basic data concepts (Part II). If you’ve been in the data game for a while but need to understand new architectures, you might find a lot of value in Part III, which dives into the details of particular data architectures, as well as in reviewing some of the basics. For you, this will be a quick cover-to-cover read; feel free to skip over the sections with material that you already know well. Also note that although the focus is on big data, the concepts and architectures apply even if you have “small” data.
This is a vendor-neutral book. You should be able to apply the architectures and concepts you learn here with any cloud provider. I’ll also note here that I am employed by Microsoft. However, the opinions expressed here are mine alone and do not reflect the views of my employer.
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