Data & AnalyticsTechnologyPlatinum

Designing a data lakehouse for unified analytics.

Data Lakehouse Designer

Delta Lake, Apache Iceberg, Apache Hudi

advancedv5.0

Best for

▸Designing medallion architecture for unified batch/streaming analytics platforms
▸Selecting between Delta Lake, Iceberg, and Hudi for multi-engine data workloads
▸Migrating from separate data lake + warehouse to unified lakehouse architecture
▸Implementing schema evolution strategies for production table formats

What you'll get

▸Comprehensive architecture decision matrix comparing table formats with specific use case recommendations and technical trade-offs
▸Detailed medallion layer specifications with partitioning strategies, retention policies, and data flow patterns
▸Schema evolution playbook with format-specific migration scripts and backward compatibility patterns

Expects

Current data architecture details, workload patterns, engine ecosystem, and specific lakehouse requirements including performance, governance, and multi-engine compatibility needs.

Returns

Detailed lakehouse architecture blueprint with table format selection rationale, medallion layer design, schema evolution strategy, and implementation roadmap with specific configurations.

What's inside

“You are a Data Lakehouse Architect. You design unified data platforms combining data lake flexibility with data warehouse reliability, delivering 40-60% cost reduction and 3-5x faster time-to-insight. - Select table formats (Delta Lake, Apache Iceberg, Apache Hudi) based on workload characteristics,...”

Covers

What You Do DifferentlyMethodologyWatch For

Not designed for ↓

×Traditional data warehouse modeling without open table formats
×Real-time streaming processing without storage layer considerations
×Basic ETL pipeline design without lakehouse-specific optimizations
×Cloud storage optimization without table format considerations

SupaScore

88.45▼

Research Quality (15%)

9.25

Prompt Engineering (25%)

8.75

Practical Utility (15%)

8.75

Completeness (10%)

8.75

User Satisfaction (20%)

8.85

Decision Usefulness (15%)

8.75

Evidence Policy

Standard: no explicit evidence policy.

data-lakehousedelta-lakeapache-icebergapache-hudimedallion-architecturetable-formattime-travelschema-evolutiondata-lakeparquetopen-table-format

Research Foundation: 8 sources (4 official docs, 2 academic, 2 industry frameworks)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.