“Extracting Data from NoSQL Databases: A Step towards Interactive Visual Analysis of NoSQL Data” is a comprehensive guide that explains the intricacies of NoSQL databases and how to extract data from them. NoSQL databases are becoming increasingly popular as they offer a flexible schema and scalability that traditional relational databases lack. However, extracting data from NoSQL databases can be a challenging task due to the lack of standardized querying language and the variety of data models used by different NoSQL databases.

The book starts with an introduction to NoSQL databases and their data models. It explains the key differences between NoSQL and relational databases, and how NoSQL databases store data in various data models such as key-value, document, column-family, and graph. The book also covers the advantages and disadvantages of using NoSQL databases, and why they are gaining popularity in the industry.

The second part of the book focuses on the various tools and techniques for extracting data from NoSQL databases. It covers the different ways to query and extract data from popular NoSQL databases like MongoDB, Cassandra, HBase, and Neo4j. The book explains how to use APIs, drivers, and libraries to connect to NoSQL databases and extract data in various formats such as JSON, CSV, and XML.

The third part of the book covers interactive visual analysis of NoSQL data. It explains how to use various data visualization tools to analyze and visualize NoSQL data. The book covers popular visualization tools like Tableau, D3.js, and Kibana, and how to integrate them with NoSQL databases for interactive data analysis.

The book concludes with a discussion on the future of NoSQL databases and how they are shaping the data landscape. It also covers the challenges and opportunities in working with NoSQL databases, and how to overcome them.

Overall, “Extracting Data from NoSQL Databases: A Step towards Interactive Visual Analysis of NoSQL Data” is an excellent resource for anyone who wants to learn about NoSQL databases, their data models, and how to extract and analyze data from them. The book is written in a clear and concise manner, and the step-by-step approach makes it easy to follow. Whether you are a data analyst, data scientist, or a database developer, this book will be a valuable addition to your library.