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BigData / Data Lake Interview questions

What are real-world Data Lake use cases and best practices?

Real-world data lake use cases span industries. E-commerce: customer 360 (unified customer view), product recommendations (collaborative filtering), inventory optimization. Healthcare: patient journey analytics, clinical research datasets, claims processing. Finance: fraud detection (real-time pattern matching), risk modeling, regulatory reporting. IoT: sensor analytics, predictive maintenance, smart cities. Best practices from production systems: start with Bronze-Silver-Gold architecture, implement comprehensive cataloging early, automate data quality checks, separate storage from compute, version all pipeline code, monitor everything (data quality, costs, performance), establish clear ownership, document extensively, test rigorously, plan for scale from day one. Success factors: executive sponsorship, cross-functional collaboration, iterative delivery, user training.

What architecture should you start with?
What is critical to implement early?

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