dataLake.hero.title
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Apache HadoopCeph S3Apache IcebergApache SparkApache KafkaTrinoApache AirflowSupersetJupyterHubMLflowKServeHBase
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Reduce reliance on proprietary Hadoop distributions and licensing constraints
Transition from HDFS-only designs to S3 lakehouse patterns
Enhance scalability, flexibility, and cost/performance predictability
Standardize governance, security, and operational visibility
Enable faster analytics delivery and AI/ML readiness
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1
Assessment & Blueprint
2-4 weeks
Inventory current platform, define target architecture
2
Foundation Build
4-8 weeks
Deploy core services, establish data zones and guardrails
3
Workload Migration
Iterative
Prioritize and migrate pipelines progressively
4
Production Hardening
Ongoing
Upgrade strategy, runbooks, managed services handoff
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dataLake.useCases.0
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