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Fundamentals of Data ObservabilityAll Indian Reprints of O'Reilly are printed in GrayscaleQuickly detect, troubleshoot, and prevent a wide range of data issues through data observability, a set of best practices that enables data teams to gain greater visibility of data and its usage. If you're a data engineer, data architect, or machine learning engineer who depends on the quality of your data, this book shows you how to focus on the practical aspects of introducing data
All Indian Reprints of O'Reilly are printed in GrayscaleQuickly detect, troubleshoot, and prevent a wide range of data issues through data observability, a set of best practices that enables data teams to gain greater visibility of data and its usage. If you're a data engineer, data architect, or machine learning engineer who depends on the quality of your data, this book shows you how to focus on the practical aspects of introducing data observability in your everyday work.Author Andy Petrella helps you build the right habits to identify and solve data issues, such as data drifts and poor quality, so you can stop their propagation in data applications, pipelines, and analytics. You'll learn ways to introduce data observability, including setting up a framework for generating and collecting all the information you need. Learn the core principles and benefits of data observability Use data observability to detect, troubleshoot, and prevent data issues Follow the book's recipes to implement observability in your data projects Use data observability to create a trustworthy communication framework with data consumers Learn how to educate your peers about the benefits of data observabilityShipping Notes
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4.8 ★★★★★
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Product Reviews
★★★★★ 5
Excellent introduction
Format: Kindle
This is a well-written introduction for quickly learning how to use Ollama to run LLMs on your local machine. The book is light on theory but very good for facilitating hands-on experimentation. Only minimal Python experience is needed. Contrary to another reviewer's comment, the source code, which can be copied from the Kindle version of the text, is also readily available by emailing the author at the address provided. The final exercise in the book leads you through generating a RAG application to use Ollama to process your own documents without having to make them available to an external server.
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Reviewed in the United States on April 6, 2026
★★★★★ 5
Effective book for learning ollama
Format: Paperback
The author has explained clearly the concept. Helpful and effectively written.
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Reviewed in the United States on January 21, 2026
★★★★★ 4
Beginners Guide to Running Your Own Private LLM
Format: Kindle
I just read this book and really enjoyed how it breaks down using Ollama as your own private LLM. It gives you just enough info to spark some cool ideas and make you want to dive deeper into AI. If you’re totally new and curious, this is a fun, easy place to start!
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Reviewed in the United States on August 4, 2025
★★★★★ 5
Lim provides an easy-to-follow path to get an LLM-powered app up and running
Format: Kindle
Lim has written another really clear, easy-to-follow tutorial. This one walked me through the Ollama platform showing step-by-step how to download open weight models, query them, supply them with my own documents, and write applications that are powered by LLMs. Lim provides an easy-to-follow path to get the first version of an LLM-powered app up and running.
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Reviewed in the United States on February 20, 2026
★★★★★ 5
Excellent roadmap for the local AI jungle
Format: Paperback
Great little book.
Every page has something useful. No fluff. Clearly written by someone whose been in the trenches lol
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Reviewed in the United States on September 23, 2025