Advanced SQL: Implementing Modern Data Solutions and ML Applications

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Bol 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

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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

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Pages: 409, Paperback, O'Reilly Media


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