SQL for Data Science: Data Cleaning, Wrangling and Analytics with Relational Databases
Publisher: Springer
৳ 450.00
📚 Book Features & Quality
🔹 Premium Paper: Off-white Karnaphuli paper, 80 GSM
🔹 Perfect Size: B5 (a little smaller than A4 but bigger than standard books)
🔹 High-Quality Print: Computer printed, sharp and clear fonts
🔹 Durable Binding: Forma binding, strong and long-lasting
🔹 Elegant Cover: Paperback, portable and attractive design
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SQL for Data Science: Data Cleaning, Wrangling, and Analytics with Relational Databases
Master SQL for Data Science & Analytics
Key Features:
SQL for Data Science – Teaches SQL within the framework of the data life cycle, covering data acquisition, cleaning, transformation, and analysis.
Practical & Hands-on Approach – Includes examples and exercises using MySQL and PostgreSQL for real-world practice.
SQL for Data Analytics – Explains how SQL can be used for data exploration, preprocessing, and basic analysis.
Integrates with R & Python – Learn how to use SQL inside Python and R for advanced data science applications.
Minimal Prerequisites – No prior knowledge of databases or data science needed—just basic computer fluency.
Ideal for aspiring data scientists, analysts, and anyone looking to harness the power of SQL for data-driven insights!
Title | SQL for Data Science: Data Cleaning, Wrangling and Analytics with Relational Databases |
|---|---|
Authors | |
Publisher | |
Edition | 1st |
Number Of Pages | 289 |
Antonio Badia, Ph.D., is an accomplished computer scientist specializing in data science, database systems, and applied data analytics. He serves as an Associate Professor in Computer Engineering and Computer Science at the University of Louisville, United States. With decades of academic and industry experience, he focuses on transforming raw data into meaningful, decision-ready insights.
His expertise covers relational database design, SQL programming, data modeling, query optimization, and modern data-management solutions. Antonio’s research also explores the integration of structured and semi-structured data, enhancing data quality, and improving database performance to support analytical and machine-learning applications.
He has authored and co-authored numerous publications and textbooks that guide students, researchers, and professionals in effectively managing and analyzing large-scale datasets. Antonio’s teaching and writing combine practical, hands-on methods with solid theoretical understanding — making complex database and analytics concepts accessible for learners at all levels.
As data-driven decision-making continues to reshape industries, Antonio Badia’s work remains highly relevant for data scientists, researchers, and organizations seeking efficient and reliable data-analytics foundations.
Springer is one of the world’s leading and longest-established academic publishers, with a heritage dating back to 1842 in Berlin. Over the decades, Springer has grown into a global powerhouse in scholarly publishing, providing high-quality research resources for universities, professionals, and scientific communities worldwide.
Springer publishes thousands of journals and a vast collection of books every year across major disciplines including science, technology, medicine, engineering, mathematics, business, social sciences, and humanities. The publisher is well-known for its strict peer-review standards and commitment to scientific accuracy and innovation.
Springer also plays a pioneering role in digital and open-access publishing, offering e-books, online research platforms, and programs that support global access to scientific knowledge. With offices and partners around the world, Springer connects researchers, scholars, and students to trusted academic content — helping drive innovation, discovery, and academic excellence.
Today, Springer remains one of the most respected and widely recognized publishers in the global research and education ecosystem.
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