--- product_id: 470009639 title: "Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines" price: "₹ 7778" currency: INR in_stock: true reviews_count: 8 url: https://www.desertcart.in/products/470009639-data-quality-fundamentals-a-practitioners-guide-to-building-trustworthy-data store_origin: IN region: India --- # Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines **Price:** ₹ 7778 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines - **How much does it cost?** ₹ 7778 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.in](https://www.desertcart.in/products/470009639-data-quality-fundamentals-a-practitioners-guide-to-building-trustworthy-data) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description Do your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck, from the data observability company Monte Carlo, explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Learn how to set and maintain data SLAs, SLIs, and SLOs Develop and lead data quality initiatives at your company Learn how to treat data services and systems with the diligence of production software Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets Review: I'm waiting for books on the next versions about data observability - As lead data engineer in a teenage software company looking to be data-driven, this book showed me the path and the current estate on data pains at scale. We're currently facing some of those. During the reading of the book, I could set the right choises on when invest on data quality frameworks. This book summarizes preetty good the actual state of data management and the key points on what you should take care if your company wants the next level of data assests. It is a should read if you're a executive or a leader who promotes data investments. This book will clear the path and the ammounth of effort that organizations needs to deal with in terms of survive and innovate. There was an item that I personally would change, that was the connection with data mesh. I trully love the all content published by Monte Carlo data, specially Barr, she is quite a data rockstar this days. I also love the book and contect on data mesh, but i felt the connection pretty forced. I'd love to see in a near future another book like this one. A book written by THE EXPERT on data quality, management, and of course observability. Review: Data Quality fundamentals - Excellent content about data quality insights, robust conceptually about Service level agreements and design strategies to ensuring the best quality. However the print quality is not the best, the plot does not have color ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | #198,660 in Books ( See Top 100 in Books ) #37 in Data Mining (Books) #69 in Data Processing #353 in Computer Software (Books) | | Customer Reviews | 4.3 out of 5 stars 45 Reviews | ## Images ![Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines - Image 1](https://m.media-amazon.com/images/I/81-wjtt+9SL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ I'm waiting for books on the next versions about data observability *by K***R on April 6, 2023* As lead data engineer in a teenage software company looking to be data-driven, this book showed me the path and the current estate on data pains at scale. We're currently facing some of those. During the reading of the book, I could set the right choises on when invest on data quality frameworks. This book summarizes preetty good the actual state of data management and the key points on what you should take care if your company wants the next level of data assests. It is a should read if you're a executive or a leader who promotes data investments. This book will clear the path and the ammounth of effort that organizations needs to deal with in terms of survive and innovate. There was an item that I personally would change, that was the connection with data mesh. I trully love the all content published by Monte Carlo data, specially Barr, she is quite a data rockstar this days. I also love the book and contect on data mesh, but i felt the connection pretty forced. I'd love to see in a near future another book like this one. A book written by THE EXPERT on data quality, management, and of course observability. ### ⭐⭐⭐⭐ Data Quality fundamentals *by D***O on July 25, 2025* Excellent content about data quality insights, robust conceptually about Service level agreements and design strategies to ensuring the best quality. However the print quality is not the best, the plot does not have color ### ⭐⭐⭐⭐⭐ This book addresses data pipeline quality in light of modern data stacks. *by W***W on November 30, 2022* Many books and tutorials have been written about “data quality” and basically what that means. However, this book takes singular aim on projects such as data pipelines, data warehousing, data integrations, business intelligence/analytics, data lakes, big data, and other types of data ETLs. It was all smartly done by the authors. The book reiterates that “many data engineering teams face “good pipelines, bad data problems; and good data pipeline infrastructures, but often with bad data”. Although I’ve searched long and hard to find a book like this to guide me in data pipeline quality and testing, this is the most comprehensive. ## Frequently Bought Together - Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines - Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness - Fundamentals of Data Engineering: Plan and Build Robust Data Systems --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.in/products/470009639-data-quality-fundamentals-a-practitioners-guide-to-building-trustworthy-data](https://www.desertcart.in/products/470009639-data-quality-fundamentals-a-practitioners-guide-to-building-trustworthy-data) --- *Product available on Desertcart India* *Store origin: IN* *Last updated: 2026-06-02*