Our editors have compiled this directory of the best data modeling books based on Amazon user reviews, rating, and ability to add business value.
There are loads of free resources available online (such as Solutions Review’s Data Analytics Software Buyer’s Guide, visual comparison matrix, and best practices section) and those are great, but sometimes it’s best to do things the old fashioned way. There are few resources that can match the in-depth, comprehensive detail of one of the best data modeling books.
The editors at Solutions Review have done much of the work for you, curating this comprehensive directory of the best data modeling books on Amazon. Titles have been selected based on the total number and quality of reader user reviews and ability to add business value. Each of the books listed in the first section of this compilation have met a minimum criteria of 15 reviews and a 4-star-or-better ranking.
Below you will find a library of titles from recognized industry analysts, experienced practitioners, and subject matter experts spanning the depths of data warehouse design all the way to designing data-intensive applications. This compilation includes publications for practitioners of all skill levels.
“The first edition of Ralph Kimball’s The Data Warehouse Toolkit introduced the industry to dimensional modeling,and now his books are considered the most authoritative guides in this space. This new third edition is a complete library of updated dimensional modeling techniques, the most comprehensive collection ever. It covers new and enhanced star schema dimensional modeling patterns, adds two new chapters on ETL techniques, includes new and expanded business matrices for 12 case studies, and more.”
“This book provides the business or IT professional with a practical working knowledge of data modelling concepts and best practices. This book is written in a conversational style that encourages you to read it from start to finish and master key objectives, including knowing when a data model is needed and which type is most effective, building a normalized relational data model, applying techniques to turn a data model into an efficient physical design, and reading a data model of any size and complexity with the same confidence as reading a book.”
“This third volume of the best-selling “Data Model Resource Book” series revolutionizes the data modeling discipline by answering the question “How can you save significant time while improving the quality of any type of data modeling effort?” In contrast to the first two volumes, this new volume focuses on the fundamental, underlying patterns that affect over 50 percent of most data modeling efforts. These patterns can be used to considerably reduce modeling time and cost, to jump-start data modeling efforts, as standards and guidelines to increase data model consistency and quality, and as an objective source against which an enterprise can evaluate data models.”
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
“Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.”
“Agile Data Warehouse Design is a step-by-step guide for capturing data warehousing / business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling + brainstorming) with BI stakeholders. The book describes BEAM, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM provides tools and techniques that will encourage DW/BI designers and developers to move away from their keyboards and entity relationship based tools and model interactively with their colleagues.”
“This book covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with “the rules”. In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness.”
“This book will teach you the simple and familiar graphical notation of COMN with its three basic shapes and four line styles, how to think about objects, concepts, types, and classes in the real world, using the ordinary meanings of English words that aren’t tangled with confused techno-speak, how to express logical data designs that are freer from implementation considerations than is possible in any other notation, and how to understand key-value, document, columnar, and table-oriented database designs in logical and physical terms.”
“Data Modeling and Database Design presents a conceptually complete coverage of indispensable topics that each MIS student should learn if that student takes only one database course. Database design and data modeling encompass the minimal set of topics addressing the core competency of knowledge students should acquire in the database area. The text, rich examples, and figures work together to cover material with a depth and precision that is not available in more introductory database books.”
“Beginning Relational Data Modeling, Second Edition will lead you step-by-step through the process of developing an effective logical data model for your relational database. No previous data modeling experience is even required. The authors infuse the book with concise, straightforward wisdom to explain a usually complex, jargon-filled discipline. And examples are based on their extensive experience modeling for real business systems. If you need to know how to capture the information needs of a business system in a relational database model, but don’t know where to start, then this is the book for you.”
“Building a Scalable Data Warehouse” covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework.”
Solutions Review participates in affiliate programs. We may make a small commission from products purchased through this resource.
- The Biggest Data Analytics News Items During the First Half of 2021 - July 22, 2021
- The Biggest Data Science News Items During the First Half of 2021 - July 22, 2021
- 2021 CRN Emerging IT Vendors: 7 Big Data Companies to Consider - July 21, 2021