SKU/Artículo: AMZ-B0FNJQ4VBJ
Advanced Data Engineering Architectures for Unified Intelligence
Format:
Kindle
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Fuera de stock
Fuera de stock
Peso con empaque:
0.15 kg
0.15 kg
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Sí
Sí
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Nuevo
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Producto de:
Amazon
Amazon
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USA
USA
Sobre este producto
- Advanced Data Engineering Architectures for Unified Intelligence An advanced strategic deep dive approach for data engineers and architects into the evolution of enterprise data from SAP to Snowflake and beyond unifying governance, AI readiness, and the future of agentic systems. Over the past several decades, the transformation of enterprise data infrastructure has been nothing short of revolutionary. This book traces the remarkable journey from traditional, monolithic relational systems to the agile, cloud-native, and AI-ready architectures known collectively as the Modern Data Stack. It is crafted for experts—seasoned architects, principal engineers, and data strategists—who demand depth, precision, and strategic insight into how the data ecosystem has evolved and where it is going. This text offers a rigorous and comprehensive exploration of how legacy systems gave way to integrated, modular architecture. Early enterprise systems relied heavily on rigid, on-premises relational databases for transactional (OLTP) processing and separate systems for analytical (OLAP) workloads. These systems were inflexible, expensive to maintain, and rarely designed to scale gracefully. The emergence of cloud-native data warehouses like Amazon Redshift introduced pay-as-you-go scalability and SQL-based, MPP analytics, ushering in a new paradigm of system flexibility and performance. As business demands intensified, organizations began adopting modular cloud-based technologies that automate stages of data processing, from ingestion through governance, unifying workflows for ingestion, storage, transformation, cataloging, and visualization. This composition of capabilities is now commonly referred to as the Modern Data Stack—an ecosystem optimized for velocity, flexibility, transparency, and democratization. Author Biography: Saradha Nagarajan Saradha Nagarajan is a senior data engineering leader transforming enterprise data into strategic advantage. With a track record of enabling AI-powered decision systems, scalable analytics platforms and award-winning business solutions, Saradha bridges the gap between data architecture and business impact. Her work in data centralization, governance, and predictive workflows continue to shape the future of intelligent, autonomous systems. From strategic pricing and marketing automation to customer retention, Saradha’s impact spans industries and continents. "I believe data should not just inform—it should inspire. When we design systems that are transparent, intelligent, and human-centered" Author Biography: Sohag Maitra Sohag Maitra is a senior data analytics leader helping financial institutions turn data into meaningful business results. With over 15 years of building successful Anti-Money Laundering systems, cloud platforms, and compliance solutions, Sohag connects advanced analytics with practical business needs and regulatory requirements. Her work in fraud detection, machine learning solutions, and data architecture continues to improve how financial services operate. From compliance automation and risk management to treasury operations and business intelligence, Sohag's leadership helps organizations across the industry achieve better performance while meeting security and regulatory standards.
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