How does Data Lake architecture facilitate data exploration and analysis?

  • Centralized data storage, Schema-on-read approach, Scalability, Flexibility
  • Data duplication, Data redundancy, Data isolation, Data normalization
  • Schema-on-write approach, Predefined schemas, Data silos, Tight integration with BI tools
  • Transactional processing, ACID compliance, Real-time analytics, High consistency
Data Lake architecture facilitates data exploration and analysis through centralized storage, a schema-on-read approach, scalability, and flexibility. This allows users to analyze diverse data sets without predefined schemas, promoting agility and innovation.
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