The guidebook "Building Modern Data Architecture with Data Lake" by Sigmoid explores the importance of data lakes in modern data architecture. It begins by defining a data lake as a centralized repository for storing large, varied datasets, essential for real-time analytics. Key components of a data lake architecture include governance, metadata, scalable storage, and DataOps. The guide contrasts data lakes with data warehouses, highlighting the flexibility and scalability of cloud-based data lakes. It also outlines best practices, such as defining long-term data goals, creating robust architecture, and embracing AI and automation. Finally, a case study demonstrates the practical benefits of implementing a data lake for a CPG firm.

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