Advanced SQL: Implementing Modern Data Solutions and ML Applications

SQL has evolved from a querying language for relational databases to a foundational tool for building scalable, modern data solutions across real-time analytics, machine learning workflows, and even generative AI applications. Advanced SQL moves beyond SELECT statements and taps into the full power of SQL as a programming interface for today's most advanced data platforms.

Written by seasoned data experts Rui Machado, Hélder Russa, and Pedro Esmeriz, this practical guide explores the role of SQL in streaming architectures (like Apache Kafka and Flink), data lake ecosystems, cloud data warehouses, and ML pipelines. Data and analytics engineers, analysts, and scientists will get hands-on guidance on expanding their SQL skills into emerging workflows and real-world production systems.

• Use SQL to design and deploy modern, end-to-end data architectures
• Integrate SQL with data lakes, stream processing, and cloud platforms
• Apply SQL in feature engineering and ML model deployment
• Master pipe syntax and other advanced query features
• Leverage SQL to build GenAI-ready data applications and pipelines

Rui Machado is a VP of Data Engineering at H&M Group. He has over a decade of experience in the architecture and implementation of data warehouses, data lakes, and decision support systems in industries such as retail, ecommerce, supply chain, healthcare, and social networks. Rui has led Engineering and Analytics teams at Jumia, Nike, and Facebook and is the coauthor of Analytics Engineering with dbt and SQL.

Hélder Russa is a Director of Data Engineering at H&M Group. He has over 10 years of experience in computer science, with an emphasis on evolving and maintaining data solutions applied to decision making. Nowadays, Hélder contributes to the strategy definition, design, and implementation of multiple H&M data platforms and products.

Pedro Esmeriz is the Head of Data Science at Maersk. He has over 8 years of experience designing and implementing predictive and prescriptive algorithms for industries such as fashion, e-commerce, supply chain, and logistics. Throughout his career, Pedro has led data science teams and the development of optimization solutions that have significantly contributed to reduced operational costs and increased revenue. He was also a co-founder of ShopAI and has played leadership roles at Maersk and Jumia, specializing in AI, ML, and MLOps frameworks.