# Data Platform Architecture Design

**Date**: 2025-01-27
**Purpose**: Design document for unified data platform
**Status**: Design Document

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## Executive Summary

This document outlines the design for a unified data platform that provides centralized data storage, analytics, and governance across all workspace projects.

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## Architecture Overview

### Components

1. **Data Lake** (MinIO, S3, or Azure Blob)
2. **Data Catalog** (Apache Atlas, DataHub, or custom)
3. **Analytics Engine** (Spark, Trino, or BigQuery)
4. **Data Pipeline** (Airflow, Prefect, or custom)
5. **Data Governance** (Policies, lineage, quality)

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## Technology Options

### Data Storage

#### Option 1: MinIO (Recommended - Self-Hosted)
- S3-compatible
- Self-hosted
- Good performance
- Cost-effective

#### Option 2: Cloudflare R2
- S3-compatible
- No egress fees
- Managed service
- Good performance

#### Option 3: Azure Blob Storage
- Azure integration
- Managed service
- Enterprise features

**Recommendation**: MinIO for self-hosted, Cloudflare R2 for cloud.

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## Data Architecture

### Data Layers

1. **Raw Layer**: Unprocessed data
2. **Cleansed Layer**: Cleaned and validated
3. **Curated Layer**: Business-ready data
4. **Analytics Layer**: Aggregated and analyzed

### Data Formats
- **Parquet**: Columnar storage
- **JSON**: Semi-structured data
- **CSV**: Tabular data
- **Avro**: Schema evolution

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## Implementation Plan

### Phase 1: Data Storage (Weeks 1-2)
- [ ] Deploy MinIO or configure cloud storage
- [ ] Set up buckets/containers
- [ ] Configure access policies
- [ ] Set up backup

### Phase 2: Data Catalog (Weeks 3-4)
- [ ] Deploy data catalog
- [ ] Register data sources
- [ ] Create data dictionary
- [ ] Set up lineage tracking

### Phase 3: Data Pipeline (Weeks 5-6)
- [ ] Set up pipeline orchestration
- [ ] Create ETL jobs
- [ ] Schedule data processing
- [ ] Monitor pipelines

### Phase 4: Analytics (Weeks 7-8)
- [ ] Set up analytics engine
- [ ] Create data models
- [ ] Build dashboards
- [ ] Set up reporting

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## Data Governance

### Policies
- Data retention policies
- Access control policies
- Privacy policies
- Quality standards

### Lineage
- Track data flow
- Document transformations
- Map dependencies
- Audit changes

### Quality
- Data validation
- Quality metrics
- Anomaly detection
- Quality reports

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## Integration

### Projects Integration
- **dbis_core**: Transaction data
- **the_order**: User data
- **Sankofa**: Platform metrics
- **All projects**: Analytics data

### API Integration
- RESTful APIs for data access
- GraphQL for queries
- Streaming APIs for real-time
- Batch APIs for bulk

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## Security

### Access Control
- Role-based access
- Data classification
- Encryption at rest
- Encryption in transit

### Privacy
- PII handling
- Data masking
- Access logging
- Compliance tracking

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## Monitoring

### Metrics
- Data ingestion rate
- Processing latency
- Storage usage
- Query performance

### Alerts
- Pipeline failures
- Quality issues
- Storage capacity
- Access anomalies

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**Last Updated**: 2025-01-27