What are some recommended books about data modeling?

There are several excellent books about data modeling that cater to different levels of expertise and cover various aspects of the subject. Here are some recommended books on data modeling:

1. "Data Modeling Essentials" by Graeme Simsion and Graham Witt:

   • This book is often considered a classic in the field. It covers fundamental concepts of data modeling, including entities, relationships, normalization, and introduces the Entity-Relationship Diagram (ERD). It is suitable for both beginners and experienced practitioners.

2. "The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling" by Ralph Kimball and Margy Ross:

   • Focused on dimensional modeling for data warehousing, this book by Kimball and Ross provides practical insights into designing effective data warehouses. It covers star schema, snowflake schema, and other concepts crucial for building data warehouses.

3. "Data Modeling for MongoDB: Building Well-Designed and Supportable MongoDB Databases" by Steve Hoberman:

   • Targeted at those working with MongoDB, this book explores data modeling techniques specifically for NoSQL databases. It covers schema design, indexing, and strategies for working with document-oriented databases.

4. "SQL and Relational Theory: How to Write Accurate SQL Code" by C.J. Date:

   • C.J. Date is a renowned expert in relational databases. In this book, he delves into the theoretical aspects of relational databases and SQL. While not focused solely on data modeling, it provides a solid foundation for understanding relational principles.

5. "Information Modeling and Relational Databases" by Terry Halpin:

   • Terry Halpin is a prominent figure in the field of conceptual modeling. This book emphasizes conceptual modeling techniques, providing insights into creating clear and understandable models before moving to logical and physical design.

6. "A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills" by Jay Wengrow:

   • While not specifically about data modeling, this book provides a practical introduction to data structures and algorithms. Understanding these concepts is essential for designing efficient data models.

7. "NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence" by Martin Fowler and Pramod J. Sadalage:

   • This book offers an overview of various NoSQL databases and their data modeling considerations. It's suitable for those interested in understanding the evolving landscape of databases beyond traditional relational systems.

8. "Building Data Models and Power Pivot for Excel" by Alberto Ferrari and Marco Russo:

   • Focused on practical aspects, this book explores data modeling using Microsoft Excel and Power Pivot. It's a hands-on guide for individuals working with data in Excel and wanting to create effective models.

Before selecting a book, consider your specific interests, the database systems you work with, and your current level of expertise. Data modeling principles are applicable across various platforms, but specialized books might be more suitable depending on your needs and the technologies you are using.