In this module, you will delve into the importance and application of relational database design principles to optimize data integrity and performance. You will explore normalization techniques to structure databases and implement key constraints to maintain data integrity. The lessons include practical exercises, such as analyzing existing database structures for improvement opportunities, and emphasize the real-world business impact of effective database design.

This module equips you with the skills to construct complex SQL queries, utilizing joins and subqueries to retrieve data from multiple tables efficiently. You will learn how to use aggregate functions and grouping techniques for data summarization, and how to evaluate and optimize SQL queries for improved performance. Through hands-on activities, you will practice these advanced querying techniques using real-world scenarios, supporting efficient data analysis in large-scale databases.

In this module, you will apply Data Definition Language (DDL) commands to create and modify database schemas, ensuring alignment with business requirements. You will learn to implement relational constraints to enforce data integrity and explore the use of Generative AI tools to assist in schema design and optimization. Through activities and practical applications, you will gain hands-on experience managing dynamic database schemas, ensuring they can adapt to evolving business needs.

This module introduces you to the concepts of data warehousing and business intelligence, focusing on the role of data warehouses in modern analytics. You will explore star schema modeling and engage in hands-on activities to create and query data warehouses. The module also covers integrating SQL Server data warehouses with business intelligence tools like Power BI to visualize trends, supporting strategic decision-making through comprehensively presented insights from warehouse data.