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Data Management at Scale: Modern Data Architecture with Data Mesh and Data Fabric 2nd Edition BY Piethein Strengholt

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In "Designing Next-Generation Data Architectures: A Practical Guide," Piethein Strengholt addresses the pressing need for organizations to evolve beyond traditional centralized data warehouses. As data management landscapes rapidly transform, the emphasis shifts towards agility and the ability to quickly derive value from data. This practical book equips executives, architects, engineers, analytics teams, and compliance professionals with the knowledge to design and implement scalable next-gen data architectures.

Strengholt's approach begins by analyzing current data management trends, such as regulatory requirements, privacy concerns, and emerging frameworks like data mesh and data fabric. These insights lay the foundation for understanding the necessity of federating responsibilities, managing data effectively, and ensuring accessibility across the organization.

Key topics covered in the book include:

Exploration of modern data architecture principles, emphasizing scalability and agility.
Detailed guidance on building cloud data landing zones, adopting domain-driven design principles, and designing data products.
In-depth examination of data governance frameworks, data security best practices, and the importance of metadata management.
Strategies for implementing master data management and establishing self-service data marketplaces to empower users.
Strengholt provides blueprints, best practices, and actionable patterns derived from real-world observations, ensuring that readers can effectively navigate the complexities of modern data ecosystems. By embracing these principles, organizations can streamline data operations, enhance compliance, and foster a culture of data-driven decision-making.

This comprehensive guide is essential for anyone involved in shaping the future of data architecture, offering practical insights that facilitate the transformation towards a scalable, agile, and value-driven data environment.
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