“SQL for Data Science: Data Cleaning, Wrangling and Analytics with Relational Databases” is a book written by SJ Sinayoko that provides a comprehensive guide to using SQL for data cleaning, wrangling, and analytics with relational databases.

The book is suitable for data analysts, data scientists, and anyone who works with large datasets and wants to learn how to use SQL to manipulate and analyze data. It assumes no prior knowledge of SQL, making it accessible to beginners, but also covers more advanced topics for experienced SQL users.

The book covers a wide range of topics related to SQL and data analysis, including:

1. Introduction to SQL and relational databases
2. Data cleaning and preprocessing using SQL
3. Data wrangling and transformation using SQL
4. Basic and advanced SQL queries for data analysis
5. Aggregation and grouping operations
6. Joining tables and subqueries
7. Window functions and analytical functions
8. Performance optimization techniques

The book also includes practical examples and code snippets to help readers apply the concepts in real-world scenarios. It emphasizes best practices in SQL development, including data modeling and schema design.

Overall, “SQL for Data Science” is a comprehensive guide to using SQL for data cleaning, wrangling, and analytics with relational databases. It is written in an accessible and easy-to-understand style and is suitable for anyone who wants to learn how to use SQL for data analysis.