SQL in a Week

This book is your fast-track pocket guide to mastering SQL, designed for absolute beginners. This step-by-step book covers everything from basic queries to advanced optimization techniques, ensuring you learn to write SQL correctly. You'll explore essential topics such as data retrieval, filtering, sorting, joins, aggregations, and data modifications, while gaining insights into performance optimization—critical for real-world applications.

The seven-day plan includes real-world scenarios, hands-on exercises, and common mistakes to avoid. While traditional SQL books focus on syntax and how to use complex functions, this book emphasizes clear, readable, and efficient query writing that applies to real-world business questions. This book is ideal for aspiring data analysts, software developers, business professionals, and job seekers preparing for SQL interviews. The book helps you develop skills that are immediately applicable and relevant in the AI age.

Written by seasoned data professionals, this book is not just about speed—it's about building habits that industry experts rely on. The book outlines the questions to expect in your busines and how to answer them. By the end of this journey, you’ll have the confidence to write robust, optimized queries that make a real impact in any database environment.

What You Will Learn

• Write SQL queries with confidence—from basic SELECT statements to complex joins, aggregations, and subqueries—so you can extract meaningful insights from any database
• Develop professional-grade SQL skills by mastering best practices for writing clean, efficient, and scalable queries that stand out in the industry
• Unlock the secrets of query optimization, indexing, and execution plans to write high-performance SQL that runs faster and more efficiently
• Apply SQL to real-world datasets across industries such as healthcare, retail, and finance, ensuring you're job-ready from day one
• Ace SQL interviews at top tech companies by practicing real-world problems, tackling optimization challenges, and avoiding common pitfalls that trip up candidates

Who this Book Is For

Absolute beginners who want to learn SQL, step by step, with a structured and practical approach. It is perfect for individuals with little to no prior experience in databases or programming, but who aspire to build a strong foundation in SQL for data-related careers.

Bhumika Shah is an accomplished engineer, PhD scholar, speaker, and educator, specializing in AI, Data Engineering, and Information Governance. With over seven years of experience, she has designed scalable data pipelines, strengthened data governance frameworks, and developed AI-driven predictive models that improve efficiency across industries. Her work has been published in peer-reviewed journals, and she is a strong advocate for leveraging AI and data engineering to enhance regulatory compliance and operational performance. She believes that data is a powerful asset—when utilized effectively, it can transform decision-making, drive innovation, and create lasting impact for businesses.

Bhumika has successfully aced over a dozen technical interviews at global companies, including MAANG firms, giving her first-hand insight into the SQL skills required to excel in real-world data roles. She has designed and taught graduate-level courses in Data Management and Analytics as a professor, equipping students with practical expertise in SQL, data governance, and cloud-based data engineering. She also actively mentors master’s degree students, helping them bridge the gap between academic theory and industry best practices.

Currently pursuing a PhD in Information Technology with a focus on exploring the impact of AI on data teams, Bhumika continues to advance research in big data analytics, business intelligence, and AI applications.

Bhumika believes SQL is a critical skill for professionals working with data, as it enables them to retrieve accurate information and transform it into actionable insights. She also emphasizes that SQL isn’t just about writing queries, but it’s about writing optimized queries that unlock efficiency and create real business impact.

Devtosh Dubey is a results-driven Senior Business Data Analyst with extensive experience in designing scalable data solutions, performing advanced statistical analyses, and leading cross-functional teams to deliver data-driven insights. With a strong PySpark, SQL, and statistical modeling background, Devtosh has optimized ETL pipelines and analytical workflows, significantly enhancing operational efficiency and supporting strategic business decisions. He has spearheaded high-impact analytical projects across healthcare and technology sectors, enabling targeted user segmentation, predictive modeling, and KPI-driven dashboard development. His work has contributed directly to revenue growth, client satisfaction, and streamlined data operations.

Devtosh is also experienced in developing production-grade dashboards, managing curated audience segmentation, and reducing data latency through efficient integration strategies. His technical toolkit includes Python, SQL, Tableau, Power BI, and AWS Redshift, with proficiency in tools such as Pandas, SciPy, and Scikit-learn. He thrives in collaborative environments, is adept at mentoring colleagues, working with external partners, and translating complex data into actionable insights that support business objectives.