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Modern Data Lakehouse Architecture
Designed a unified data architecture that combines batch and streaming workloads to support scalable analytics and enterprise reporting.
Context
Enterprises were managing fragmented data systems across warehouses, lakes, and streaming platforms.
Challenge
Lack of unified architecture created duplication, inconsistent metrics, and slow analytics workflows.
Approach
Unified ingestion layer for batch and streaming data
Centralized storage layer for structured and semi-structured data
Analytics layer optimized for reporting and BI workloads
Architecture Overview
Data Sources
↓
Ingestion Layer (Batch + Streaming)
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Lakehouse Storage Layer
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Processing & Transformation
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Analytics & BI Layer
Outcome
Unified data architecture across teams
Improved data consistency and reliability
Faster analytics workflows
Reduced system fragmentation across platforms