{"product_id":"data-quality-concepts-methodologies-and-techniques-essential","title":"Data Quality: Concepts, Methodologies and Techniques - Essential","description":"\u003cp\u003eIn this review of Data Quality: Concepts, Methodologies and Techniques the bottom line is clear: this book is a rigorous, research-driven introduction to the theory and practice of data quality aimed at professionals and advanced students who need a systematic foundation. It delivers a broad survey of parameters, techniques and methodologies drawn from core data quality research and adjacent fields, and it is most valuable for readers who want conceptual depth rather than a quick how-to manual. The text reads like an academic reference that also points to practical methods for diagnosis and improvement.\u003c\/p\u003e\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComprehensive introduction:\u003c\/strong\u003e The book maps the wide array of data quality issues so readers can understand the scope and interdependencies of common problems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eParameter-focused framework:\u003c\/strong\u003e Detailed description of data quality parameters helps practitioners identify which dimensions matter for their systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCross-disciplinary techniques:\u003c\/strong\u003e Methods from data mining, probability, statistics and machine learning are presented to give multiple approaches to quality assessment.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eState-of-the-art overview:\u003c\/strong\u003e The text reviews current research and methodologies, making it a useful entry point to academic and applied literature.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eCritical perspective:\u003c\/strong\u003e The authors include critical discussion of techniques and limitations, encouraging readers to evaluate methods rather than accept them uncritically.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eWho It's For\u003c\/h2\u003e\n\u003cp\u003eThis book suits data engineers, data quality analysts, researchers and graduate students who need a systematic, theory-grounded treatment of data quality. It is particularly valuable for those designing data governance, validation and cleansing strategies and for professionals seeking to align technical solutions with regulatory or organizational requirements.\u003c\/p\u003e\n\u003cp\u003eReaders looking for quick, hands-on tutorials, tool-specific guidance or brief checklists should look elsewhere; this volume emphasizes concepts and methodologies over step-by-step recipes and product recommendations.\u003c\/p\u003e\n\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eThorough conceptual coverage provides a solid foundation for designing data quality programs.\u003c\/li\u003e\n\u003cli\u003eInterdisciplinary treatment brings together useful techniques from related fields for practical use.\u003c\/li\u003e\n\u003cli\u003eClear description of data quality parameters aids in precise assessment and benchmarking.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eNot a quick reference or hands-on guide; readers expecting tool-specific steps may be disappointed.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eData Quality: Concepts, Methodologies and Techniques\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSeries\u003c\/td\u003e\n\u003ctd\u003eData-Centric Systems and Applications\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAuthors\u003c\/td\u003e\n\u003ctd\u003eCarlo Batini, Monica Scannapieco\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eScope\u003c\/td\u003e\n\u003ctd\u003eComprehensive introduction to data quality concepts and techniques\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eApproach\u003c\/td\u003e\n\u003ctd\u003eAcademic survey with practical methodological pointers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDisciplines covered\u003c\/td\u003e\n\u003ctd\u003eData mining, probability theory, statistics, machine learning\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\u003ch2\u003eOur Verdict\u003c\/h2\u003e\n\u003cp\u003eFor practitioners and students who need a deep, methodical grounding in data quality, this book is a strong investment: it organizes the field's parameters, surveys relevant techniques and encourages critical evaluation of methods. It offers good value for readers who want durable conceptual tools rather than transient software tips.\u003c\/p\u003e\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eIs this book practical for day-to-day data cleaning?\u003c\/strong\u003e\u003cbr\u003eThe book provides methodologies and principles that inform cleaning decisions, but it does not serve as a step-by-step tool manual.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eDoes the book cover machine learning approaches?\u003c\/strong\u003e\u003cbr\u003eYes, it includes techniques and perspectives from machine learning alongside statistical and data mining methods.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWho wrote the book and what perspective do they bring?\u003c\/strong\u003e\u003cbr\u003eThe authors are Carlo Batini and Monica Scannapieco, and they present a research-informed, critical perspective on data quality.\u003c\/p\u003e","brand":"Carlo Batini, Monica Scannapieco","offers":[{"title":"Default Title","offer_id":48155463254235,"sku":"3642069703","price":107.29,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/61pEZEMqqYL._SL1248.jpg?v=1768866694","url":"https:\/\/gearmusthave.com\/products\/data-quality-concepts-methodologies-and-techniques-essential","provider":"GearMustHave","version":"1.0","type":"link"}